WorldWideScience

Sample records for human decision modeling

  1. Integrated Environmental Modelling: human decisions, human challenges

    Science.gov (United States)

    Glynn, Pierre D.

    2015-01-01

    Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.

  2. Human-centric decision-making models for social sciences

    CERN Document Server

    Pedrycz, Witold

    2014-01-01

    The volume delivers a wealth of effective methods to deal with various types of uncertainty inherently existing in human-centric decision problems. It elaborates on  comprehensive decision frameworks to handle different decision scenarios, which help use effectively the explicit and tacit knowledge and intuition, model perceptions and preferences in a more human-oriented style. The book presents original approaches and delivers new results on fundamentals and applications related to human-centered decision making approaches to business, economics and social systems. Individual chapters cover multi-criteria (multiattribute) decision making, decision making with prospect theory, decision making with incomplete probabilistic information, granular models of decision making and decision making realized with the use of non-additive measures. New emerging decision theories being presented as along with a wide spectrum of ongoing research make the book valuable to all interested in the field of advanced decision-mak...

  3. A control-theory model for human decision-making

    Science.gov (United States)

    Levison, W. H.; Tanner, R. B.

    1971-01-01

    A model for human decision making is an adaptation of an optimal control model for pilot/vehicle systems. The models for decision and control both contain concepts of time delay, observation noise, optimal prediction, and optimal estimation. The decision making model was intended for situations in which the human bases his decision on his estimate of the state of a linear plant. Experiments are described for the following task situations: (a) single decision tasks, (b) two-decision tasks, and (c) simultaneous manual control and decision making. Using fixed values for model parameters, single-task and two-task decision performance can be predicted to within an accuracy of 10 percent. Agreement is less good for the simultaneous decision and control situation.

  4. A control theory model for human decision making

    Science.gov (United States)

    Levison, W. H.

    1972-01-01

    The optimal control model for pilot-vehicle systems has been extended to handle certain types of human decision tasks. The model for decision making incorporates the observation noise, optimal estimation, and prediction concepts that form the basis of the model for control behavior. Experiments are described for the following task situations: (1) single decision tasks; (2) two decision tasks; and (3) simultaneous manual control and decision tasks. Using fixed values for model parameters, single-task and two-task decision performance scores to within an accuracy of 10 percent can be predicted. The experiment on simultaneous control and decision indicates the presence of task interference in this situation, but the results are not adequate to allow a conclusive test of the predictive capability of the model.

  5. Simulation Models of Human Decision-Making Processes

    Directory of Open Access Journals (Sweden)

    Nina RIZUN

    2014-10-01

    Full Text Available The main purpose of the paper is presentation of the new concept of human decision-making process modeling via using the analogy with Automatic Control Theory. From the author's point of view this concept allows to develop and improve the theory of decision-making in terms of the study and classification of specificity of the human intellectual processes in different conditions. It was proved that the main distinguishing feature between the Heuristic / Intuitive and Rational Decision-Making Models is the presence of so-called phenomenon of "enrichment" of the input information with human propensity, hobbies, tendencies, expectations, axioms and judgments, presumptions or bias and their justification. In order to obtain additional knowledge about the basic intellectual processes as well as the possibility of modeling the decision results in various parameters characterizing the decision-maker, the complex of the simulation models was developed. These models are based on the assumptions that:  basic intellectual processes of the Rational Decision-Making Model can be adequately simulated and identified by the transient processes of the proportional-integral-derivative controller; basic intellectual processes of the Bounded Rationality and Intuitive Models can be adequately simulated and identified by the transient processes of the nonlinear elements.The taxonomy of the most typical automatic control theory elements and their compliance with certain decision-making models with a point of view of decision-making process specificity and decision-maker behavior during a certain time of professional activity was obtained.

  6. Modelling Human Emotions for Tactical Decision-Making Games

    Science.gov (United States)

    Visschedijk, Gillian C.; Lazonder, Ard W.; van der Hulst, Anja; Vink, Nathalie; Leemkuil, Henny

    2013-01-01

    The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studies were performed to investigate the relation between fidelity and human emotion recognition in virtual human characters. Study 1 compared five versions of a virtual…

  7. Modelling human emotions for tactical decision-making games

    NARCIS (Netherlands)

    Visschedijk, G.C.; Lazonder, A.W.; Hulst, A.H. van der; Vink, N.; Leemkuil, H.

    2013-01-01

    The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studieswere performed to investigate the relation between fidelity and human emotion recognition in virtual human characte

  8. Modelling human emotions for tactical decision-making games

    NARCIS (Netherlands)

    Visschedijk, G.C.; Lazonder, A.W.; Hulst, A.H. van der; Vink, N.; Leemkuil, H.

    2013-01-01

    The training of tactical decision making increasingly occurs through serious computer games. A challenging aspect of designing such games is the modelling of human emotions. Two studieswere performed to investigate the relation between fidelity and human emotion recognition in virtual human characte

  9. Modeling human decision making behavior in supervisory control

    Science.gov (United States)

    Tulga, M. K.; Sheridan, T. B.

    1977-01-01

    An optimal decision control model was developed, which is based primarily on a dynamic programming algorithm which looks at all the available task possibilities, charts an optimal trajectory, and commits itself to do the first step (i.e., follow the optimal trajectory during the next time period), and then iterates the calculation. A Bayesian estimator was included which estimates the tasks which might occur in the immediate future and provides this information to the dynamic programming routine. Preliminary trials comparing the human subject's performance to that of the optimal model show a great similarity, but indicate that the human skips certain movements which require quick change in strategy.

  10. Modelling human decision-making in coupled human and natural systems

    Science.gov (United States)

    Feola, G.

    2012-12-01

    A solid understanding of human decision-making is essential to analyze the complexity of coupled human and natural systems (CHANS) and inform policies to promote resilience in the face of environmental change. Human decisions drive and/or mediate the interactions and feedbacks, and contribute to the heterogeneity and non-linearity that characterize CHANS. However, human decision-making is usually over-simplistically modeled, whereby human agents are represented deterministically either as dumb or clairvoyant decision-makers. Decision-making models fall short in the integration of both environmental and human behavioral drivers, and concerning the latter, tend to focus on only one category, e.g. economic, cultural, or psychological. Furthermore, these models render a linear decision-making process and therefore fail to account for the recursive co-evolutionary dynamics in CHANS. As a result, these models constitute only a weak basis for policy-making. There is therefore scope and an urgent need for better approaches to human decision-making, to produce the knowledge that can inform vulnerability reduction policies in the face of environmental change. This presentation synthesizes the current state-of-the-art of modelling human decision-making in CHANS, with particular reference to agricultural systems, and delineates how the above mentioned shortcomings can be overcome. Through examples from research on pesticide use and adaptation to climate change, both based on the integrative agent-centered framework (Feola and Binder, 2010), the approach for an improved understanding of human agents in CHANS are illustrated. This entails: integrative approach, focus on behavioral dynamics more than states, feedbacks between individual and system levels, and openness to heterogeneity.

  11. Aiding human reliance decision making using computational models of trust

    NARCIS (Netherlands)

    Maanen, P.P. van; Klos, T.; Dongen, C.J. van

    2007-01-01

    This paper involves a human-agent system in which there is an operator charged with a pattern recognition task, using an automated decision aid. The objective is to make this human-agent system operate as effectively as possible. Effectiveness is gained by an increase of appropriate reliance on the

  12. Model of human collective decision-making in complex environments

    Science.gov (United States)

    Carbone, Giuseppe; Giannoccaro, Ilaria

    2015-12-01

    A continuous-time Markov process is proposed to analyze how a group of humans solves a complex task, consisting in the search of the optimal set of decisions on a fitness landscape. Individuals change their opinions driven by two different forces: (i) the self-interest, which pushes them to increase their own fitness values, and (ii) the social interactions, which push individuals to reduce the diversity of their opinions in order to reach consensus. Results show that the performance of the group is strongly affected by the strength of social interactions and by the level of knowledge of the individuals. Increasing the strength of social interactions improves the performance of the team. However, too strong social interactions slow down the search of the optimal solution and worsen the performance of the group. In particular, we find that the threshold value of the social interaction strength, which leads to the emergence of a superior intelligence of the group, is just the critical threshold at which the consensus among the members sets in. We also prove that a moderate level of knowledge is already enough to guarantee high performance of the group in making decisions.

  13. Integrating human and robot decision-making dynamics with feedback : Models and convergence analysis

    NARCIS (Netherlands)

    Cao, Ming; Stewart, Andrew; Leonard, Naomi Ehrich

    2008-01-01

    Leveraging research by psychologists on human decision-making, we present a human-robot decision-making problem associated with a complex task and study the corresponding joint decision-making dynamics. The collaborative task is designed so that the human makes decisions just as human subjects make

  14. A conceptual and computational model of moral decision making in human and artificial agents.

    Science.gov (United States)

    Wallach, Wendell; Franklin, Stan; Allen, Colin

    2010-07-01

    Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we

  15. Computer-Aided Decisions in Human Services: Expert Systems and Multivariate Models.

    Science.gov (United States)

    Sicoly, Fiore

    1989-01-01

    This comparison of two approaches to the development of computerized supports for decision making--expert systems and multivariate models--focuses on computerized systems that assist professionals with tasks related to diagnosis or classification in human services. Validation of both expert systems and statistical models is emphasized. (39…

  16. A decision model for the sustainable protection of human rights in Italian Prison System

    Directory of Open Access Journals (Sweden)

    Antonio Maturo

    2014-12-01

    Full Text Available The work starts from an analysis of the critical problems of the prison system in Italy. It aims to develop a decision-making model to address the issue of sustainable protection of human rights in prisons. It shows how, using the Saaty AHP procedure, it is possible to have an analytical reasoning guideline for the understanding of the validity of the various alternative choices, in order to facilitate the situation of the prisoners and their reintegration into society.

  17. A cortical network model of cognitive and emotional influences in human decision making.

    Science.gov (United States)

    Nazir, Azadeh Hassannejad; Liljenström, Hans

    2015-10-01

    Decision making (DM)(2) is a complex process that appears to involve several brain structures. In particular, amygdala, orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) seem to be essential in human decision making, where both emotional and cognitive aspects are taken into account. In this paper, we present a computational network model representing the neural information processing of DM, from perception to behavior. We model the population dynamics of the three neural structures (amygdala, OFC and LPFC), as well as their interaction. In our model, the neurodynamic activity of amygdala and OFC represents the neural correlates of secondary emotion, while the activity of certain neural populations in OFC alone represents the outcome expectancy of different options. The cognitive/rational aspect of DM is associated with LPFC. Our model is intended to give insights on the emotional and cognitive processes involved in DM under various internal and external contexts. Different options for actions are represented by the oscillatory activity of cell assemblies, which may change due to experience and learning. Knowledge and experience of the outcome of our decisions and actions can eventually result in changes in our neural structures, attitudes and behaviors. Simulation results may have implications for how we make decisions for our individual actions, as well as for societal choices, where we take examples from transport and its impact on CO2 emissions and climate change.

  18. Design strategies for human & earth systems modeling to meet emerging multi-scale decision support needs

    Science.gov (United States)

    Spak, S.; Pooley, M.

    2012-12-01

    The next generation of coupled human and earth systems models promises immense potential and grand challenges as they transition toward new roles as core tools for defining and living within planetary boundaries. New frontiers in community model development include not only computational, organizational, and geophysical process questions, but also the twin objectives of more meaningfully integrating the human dimension and extending applicability to informing policy decisions on a range of new and interconnected issues. We approach these challenges by posing key policy questions that require more comprehensive coupled human and geophysical models, identify necessary model and organizational processes and outputs, and work backwards to determine design criteria in response to these needs. We find that modular community earth system model design must: * seamlessly scale in space (global to urban) and time (nowcasting to paleo-studies) and fully coupled on all component systems * automatically differentiate to provide complete coupled forward and adjoint models for sensitivity studies, optimization applications, and 4DVAR assimilation across Earth and human observing systems * incorporate diagnostic tools to quantify uncertainty in couplings, and in how human activity affects them * integrate accessible community development and application with JIT-compilation, cloud computing, game-oriented interfaces, and crowd-sourced problem-solving We outline accessible near-term objectives toward these goals, and describe attempts to incorporate these design objectives in recent pilot activities using atmosphere-land-ocean-biosphere-human models (WRF-Chem, IBIS, UrbanSim) at urban and regional scales for policy applications in climate, energy, and air quality.

  19. A critical meta-analysis of lens model studies in human judgment and decision-making.

    Science.gov (United States)

    Kaufmann, Esther; Reips, Ulf-Dietrich; Wittmann, Werner W

    2013-01-01

    Achieving accurate judgment ('judgmental achievement') is of utmost importance in daily life across multiple domains. The lens model and the lens model equation provide useful frameworks for modeling components of judgmental achievement and for creating tools to help decision makers (e.g., physicians, teachers) reach better judgments (e.g., a correct diagnosis, an accurate estimation of intelligence). Previous meta-analyses of judgment and decision-making studies have attempted to evaluate overall judgmental achievement and have provided the basis for evaluating the success of bootstrapping (i.e., replacing judges by linear models that guide decision making). However, previous meta-analyses have failed to appropriately correct for a number of study design artifacts (e.g., measurement error, dichotomization), which may have potentially biased estimations (e.g., of the variability between studies) and led to erroneous interpretations (e.g., with regards to moderator variables). In the current study we therefore conduct the first psychometric meta-analysis of judgmental achievement studies that corrects for a number of study design artifacts. We identified 31 lens model studies (N = 1,151, k = 49) that met our inclusion criteria. We evaluated overall judgmental achievement as well as whether judgmental achievement depended on decision domain (e.g., medicine, education) and/or the level of expertise (expert vs. novice). We also evaluated whether using corrected estimates affected conclusions with regards to the success of bootstrapping with psychometrically-corrected models. Further, we introduce a new psychometric trim-and-fill method to estimate the effect sizes of potentially missing studies correct psychometric meta-analyses for effects of publication bias. Comparison of the results of the psychometric meta-analysis with the results of a traditional meta-analysis (which only corrected for sampling error) indicated that artifact correction leads to a) an

  20. Towards Human-Robot Teams : Model-Based Analysis of Human Decision Making in Two-Alternative Choice Tasks With Social Feedback

    NARCIS (Netherlands)

    Stewart, Andrew; Cao, Ming; Nedic, Andrea; Tomlin, Damon; Leonard, Naomi Ehrich

    2012-01-01

    With a principled methodology for systematic design of human-robot decision-making teams as a motivating goal, we seek an analytic, model-based description of the influence of team and network design parameters on decision-making performance. Given that there are few reliably predictive models of hu

  1. Modelling Interactions between forest pest invasions and human decisions regarding firewood transport restrictions.

    Directory of Open Access Journals (Sweden)

    Lee-Ann Barlow

    Full Text Available The invasion of nonnative, wood-boring insects such as the Asian longhorned beetle (A. glabripennis and the emerald ash borer (A. planipennis is a serious ecological and economic threat to Canadian deciduous and mixed-wood forests. Humans act as a major vector for the spread of these pests via firewood transport, although existing models do not explicitly capture human decision-making regarding firewood transport. In this paper we present a two-patch coupled human-environment system model that includes social influence and long-distance firewood transport and examines potential strategies for mitigating pest spread. We found that increasing concern regarding infestations (f significantly reduced infestation. Additionally it resulted in multiple thresholds at which the intensity of infestation in a patch was decreased. It was also found that a decrease in the cost of firewood purchased in the area where it is supposed to be burned (Cl resulted in an increased proportion of local-firewood strategists, and a 67% decrease in Cl from $6.75 to $4.50 was sufficient to eliminate crosspatch infestation. These effects are synergistic: increasing concern through awareness and education campaigns acts together with reduced firewood costs, thereby reducing the required threshold of both awareness and economic incentives. Our results indicate that the best management strategy includes a combination of public education paired with firewood subsidization.

  2. The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Human Space Flight Missions

    Science.gov (United States)

    Kerstman, Eric L.; Minard, Charles; FreiredeCarvalho, Mary H.; Walton, Marlei E.; Myers, Jerry G., Jr.; Saile, Lynn G.; Lopez, Vilma; Butler, Douglas J.; Johnson-Throop, Kathy A.

    2011-01-01

    This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed.

  3. Cortical and hippocampal correlates of deliberation during model-based decisions for rewards in humans.

    Directory of Open Access Journals (Sweden)

    Aaron M Bornstein

    Full Text Available How do we use our memories of the past to guide decisions we've never had to make before? Although extensive work describes how the brain learns to repeat rewarded actions, decisions can also be influenced by associations between stimuli or events not directly involving reward - such as when planning routes using a cognitive map or chess moves using predicted countermoves - and these sorts of associations are critical when deciding among novel options. This process is known as model-based decision making. While the learning of environmental relations that might support model-based decisions is well studied, and separately this sort of information has been inferred to impact decisions, there is little evidence concerning the full cycle by which such associations are acquired and drive choices. Of particular interest is whether decisions are directly supported by the same mnemonic systems characterized for relational learning more generally, or instead rely on other, specialized representations. Here, building on our previous work, which isolated dual representations underlying sequential predictive learning, we directly demonstrate that one such representation, encoded by the hippocampal memory system and adjacent cortical structures, supports goal-directed decisions. Using interleaved learning and decision tasks, we monitor predictive learning directly and also trace its influence on decisions for reward. We quantitatively compare the learning processes underlying multiple behavioral and fMRI observables using computational model fits. Across both tasks, a quantitatively consistent learning process explains reaction times, choices, and both expectation- and surprise-related neural activity. The same hippocampal and ventral stream regions engaged in anticipating stimuli during learning are also engaged in proportion to the difficulty of decisions. These results support a role for predictive associations learned by the hippocampal memory system to

  4. Mathematical Decision Models Applied for Qualifying and Planning Areas Considering Natural Hazards and Human Dealing

    Science.gov (United States)

    Anton, Jose M.; Grau, Juan B.; Tarquis, Ana M.; Sanchez, Elena; Andina, Diego

    2014-05-01

    The authors were involved in the use of some Mathematical Decision Models, MDM, to improve knowledge and planning about some large natural or administrative areas for which natural soils, climate, and agro and forest uses where main factors, but human resources and results were important, natural hazards being relevant. In one line they have contributed about qualification of lands of the Community of Madrid, CM, administrative area in centre of Spain containing at North a band of mountains, in centre part of Iberian plateau and river terraces, and also Madrid metropolis, from an official study of UPM for CM qualifying lands using a FAO model from requiring minimums of a whole set of Soil Science criteria. The authors set first from these criteria a complementary additive qualification, and tried later an intermediate qualification from both using fuzzy logic. The authors were also involved, together with colleagues from Argentina et al. that are in relation with local planners, for the consideration of regions and of election of management entities for them. At these general levels they have adopted multi-criteria MDM, used a weighted PROMETHEE, and also an ELECTRE-I with the same elicited weights for the criteria and data, and at side AHP using Expert Choice from parallel comparisons among similar criteria structured in two levels. The alternatives depend on the case study, and these areas with monsoon climates have natural hazards that are decisive for their election and qualification with an initial matrix used for ELECTRE and PROMETHEE. For the natural area of Arroyos Menores at South of Rio Cuarto town, with at North the subarea of La Colacha, the loess lands are rich but suffer now from water erosions forming regressive ditches that are spoiling them, and use of soils alternatives must consider Soil Conservation and Hydraulic Management actions. The use of soils may be in diverse non compatible ways, as autochthonous forest, high value forest, traditional

  5. Applying an agent-based model of agricultural terraces coupled with a landscape evolution model to explore the impact of human decision-making on terraced terrain

    Science.gov (United States)

    Glaubius, Jennifer

    2016-04-01

    Agricultural terraces impact landscape evolution as a result of long-term human-landscape interactions, including decisions regarding terrace maintenance and abandonment. Modeling simulations are often employed to examine the sensitivity of landscapes to various factors, such as rainfall and land cover. Landscape evolution models, erosion models, and hydrological models have all previously been used to simulate the impact of agricultural terrace construction on terrain evolution, soil erosion, and hydrological connectivity. Human choices regarding individual terraces have not been included in these models to this point, despite recent recognition that maintenance and abandonment decisions alter transport and storage patterns of soil and water in terraced terrain. An agent-based model of human decisions related to agricultural terraces is implemented based on a conceptual model of agricultural terrace life cycle stages created from a literature review of terracing impacts. The agricultural terracing agent-based model is then coupled with a landscape evolution model to explore the role of human decisions in the evolution of terraced landscapes. To fully explore this type of co-evolved landscape, human decision-making and its feedbacks must be included in landscape evolution models. Project results may also have implications for management of terraced terrain based on how human choices in these environments affect soil loss and land degradation.

  6. A model of human collective decision-making in complex environments

    CERN Document Server

    Carbone, Giuseppe

    2015-01-01

    A continuous-time Markov process is proposed to analyze how a group of humans solves a complex task, consisting in the search of the optimal set of decisions on a fitness landscape. Individuals change their opinions driven by two different forces: (i) the rational behavior which pushes them to change their opinions as to increase their own fitness values, and (ii) the social interactions which push individuals to reduce the diversity of their opinions in order to reach consensus. Results show that the performance of the group is strongly affected by the strength of social interactions and by the level of knowledge of the individuals. Increasing the strength of social interactions improves the performance of the team. However, too strong social interactions slow down the search of the optimal solution and worsen the performance of the group. We prove that a moderate level of knowledge is already enough to guarantee high performance of the group in making decisions.

  7. A simple artificial life model explains irrational behavior in human decision-making.

    Directory of Open Access Journals (Sweden)

    Carolina Feher da Silva

    Full Text Available Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

  8. Flawed Assumptions, Models and Decision Making: Misconceptions Concerning Human Elements in Complex System

    Energy Technology Data Exchange (ETDEWEB)

    FORSYTHE,JAMES C.; WENNER,CAREN A.

    1999-11-03

    The history of high consequence accidents is rich with events wherein the actions, or inaction, of humans was critical to the sequence of events preceding the accident. Moreover, it has been reported that human error may contribute to 80% of accidents, if not more (dougherty and Fragola, 1988). Within the safety community, this reality is widely recognized and there is a substantially greater awareness of the human contribution to system safety today than has ever existed in the past. Despite these facts, and some measurable reduction in accident rates, when accidents do occur, there is a common lament. No matter how hard we try, we continue to have accidents. Accompanying this lament, there is often bewilderment expressed in statements such as, ''There's no explanation for why he/she did what they did''. It is believed that these statements are a symptom of inadequacies in how they think about humans and their role within technological systems. In particular, while there has never been a greater awareness of human factors, conceptual models of human involvement in engineered systems are often incomplete and in some cases, inaccurate.

  9. Real Life Decision Optimization Model

    OpenAIRE

    Raju, Naga; Reddy, Diwakar; Reddy, Rajeswara; Krishnaiah, G

    2016-01-01

    In real life scientific and engineering problems decision making is common practice. Decision making include single decision maker or group of decision makers. Decision maker’s expressions consists imprecise, inconsistent and indeterminate information. Also, the decision maker cannot select the best solution in unidirectional (single goal) way. Therefore, proposed model adopts decision makers’ opinions in Neutrosophic Values (SVNS/INV) which effectively deals imprecise, inconsistent and indet...

  10. Planning, Decisions, and Human Nature.

    Science.gov (United States)

    Keller, George

    1998-01-01

    Brings the perspectives of five individuals (Sigmund Freud, Karl Marx, Charles Darwin, Johann von Herder, James Madison) to the question of why humans behave as they do when faced with the need for decision making and change in higher education. Argues that effecting change is easier if leaders attend to the concerns and fears of those affected by…

  11. Planning, Decisions, and Human Nature.

    Science.gov (United States)

    Keller, George

    1998-01-01

    Brings the perspectives of five individuals (Sigmund Freud, Karl Marx, Charles Darwin, Johann von Herder, James Madison) to the question of why humans behave as they do when faced with the need for decision making and change in higher education. Argues that effecting change is easier if leaders attend to the concerns and fears of those affected by…

  12. Decision science a human-oriented perspective

    CERN Document Server

    Mengov, George

    2015-01-01

    This book offers a new perspective on human decision-making by comparing the established methods in decision science with innovative modelling at the level of neurons and neural interactions. The book presents a new generation of computer models, which can predict with astonishing accuracy individual economic choices when people make them by quick intuition rather than by effort. A vision for a new kind of social science is outlined, whereby neural models of emotion and cognition capture the dynamics of socioeconomic systems and virtual social networks. The exposition is approachable by experts as well as by advanced students. The author is an Associate Professor of Decision Science with a doctorate in Computational Neuroscience, and a former software consultant to banks in the City of London.  .

  13. Simulation of human decision making

    Science.gov (United States)

    Forsythe, J. Chris; Speed, Ann E.; Jordan, Sabina E.; Xavier, Patrick G.

    2008-05-06

    A method for computer emulation of human decision making defines a plurality of concepts related to a domain and a plurality of situations related to the domain, where each situation is a combination of at least two of the concepts. Each concept and situation is represented in the computer as an oscillator output, and each situation and concept oscillator output is distinguishable from all other oscillator outputs. Information is input to the computer representative of detected concepts, and the computer compares the detected concepts with the stored situations to determine if a situation has occurred.

  14. Dual learning processes underlying human decision-making in reversal learning tasks: Functional significance and evidence from the model fit to human behavior

    Directory of Open Access Journals (Sweden)

    Yu eBai

    2014-08-01

    Full Text Available Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against mistuning of parameters compared to the standard RL model when decision makers continue to learn stimulus-reward contingencies, which make an abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model.

  15. Decision making models and human factors: TOPSIS and Ergonomic Behaviors (TOPSIS-EB

    Directory of Open Access Journals (Sweden)

    Mohammad

    2017-02-01

    Full Text Available An effective safety management requires attention to human factors as well as system compo-nents which make risky or safe situations at technical components. This study evaluates and ana-lyze ergonomic behaviors in order to select the best work shift group in an Iranian process in-dustry, in 2010.The methodology was based on the Ergonomic Behavior Sampling (EBS, and TOPSIS method. After specifying the unergonomic behaviors and with reference to the results of a pilot study, a sample of 1755 was determined, with a sampling accuracy of 5% and confi-dence level of 95%. However, in order to gain more confidence, 2631 observations were collect-ed. The results indicate that 43.6% of workers’ behaviors were unergonomic. The most frequent unergonomic behavior was amusing of legs while load lifting with 83.01% of total unergonomic behaviors observations. Using TOPSIS method, the most effective shift group and the least at-tractive alternatives for intervention were selected in this company. Findings declare high number of unergonomic behaviors. Catastrophic consequences of accidents in petrochemical industry ne-cessitate attention to workers’ ergonomic behaviors in the workplace and promotion of them.

  16. Assessment of human decision reliability - a case study

    Energy Technology Data Exchange (ETDEWEB)

    Pyy, P

    1998-07-01

    In his discussion of this case study, the author indicates that human beings are not merely machines who use rules. Thus, more focus needs to be put on studying decision making situations and their contexts. Decision theory (both normative and descriptive) and contextual psychological approaches may offer tools to cope with operator decision making. Further an ideal decision space needs to be defined for operators. The case study specifically addressed a loss of feedwater scenario and the various operator decisions that were involved in that scenario. It was concluded from this particular study that there are significant differences in the crew decision behaviours that are not explained by process variables. Through use of evidence from simulator tests with expert judgement, an approach to estimate probabilities has been developed. The modelling approach presented in this discussion is an extension of current HRA paradigms, but a natural one since all human beings make decisions.

  17. Issues in Strategic Decision Modelling

    CERN Document Server

    Jennings, Paula

    2008-01-01

    [Spreadsheet] Models are invaluable tools for strategic planning. Models help key decision makers develop a shared conceptual understanding of complex decisions, identify sensitivity factors and test management scenarios. Different modelling approaches are specialist areas in themselves. Model development can be onerous, expensive, time consuming, and often bewildering. It is also an iterative process where the true magnitude of the effort, time and data required is often not fully understood until well into the process. This paper explores the traditional approaches to strategic planning modelling commonly used in organisations and considers the application of a real-options approach to match and benefit from the increasing uncertainty in today's rapidly changing world.

  18. Handbook of Marketing Decision Models

    NARCIS (Netherlands)

    B. Wierenga (Berend)

    2008-01-01

    textabstractThis book presents the state of the art in marketing decision models, dealing with new modeling areas such as customer relationship management, customer value and online marketing, but also describes recent developments in other areas. In the category of marketing mix models, the latest

  19. Handbook of Marketing Decision Models

    NARCIS (Netherlands)

    B. Wierenga (Berend)

    2008-01-01

    textabstractThis book presents the state of the art in marketing decision models, dealing with new modeling areas such as customer relationship management, customer value and online marketing, but also describes recent developments in other areas. In the category of marketing mix models, the latest

  20. Following Human Footsteps: Proposal of a Decision Theory Based on Human Behavior

    Science.gov (United States)

    Mahmud, Faisal

    2011-01-01

    Human behavior is a complex nature which depends on circumstances and decisions varying from time to time as well as place to place. The way a decision is made either directly or indirectly related to the availability of the options. These options though appear at random nature, have a solid directional way for decision making. In this paper, a decision theory is proposed which is based on human behavior. The theory is structured with model sets that will show the all possible combinations for making a decision, A virtual and simulated environment is considered to show the results of the proposed decision theory

  1. A Model of Human Decision Making in Complex Systems and its Use for Design of System Control Strategies

    DEFF Research Database (Denmark)

    Rasmussen, Jens; Lind, Morten

    The paper describes a model of operators' decision making in complex system control, based on studies of event reports and performance in control rooms. This study shows how operators base their decisions on knowledge of system properties at different levels of abstraction depending...... on their perception of the system's immediate control requirements. These levels correspond to the abstraction hierarchy including system purpose, functions, and physical details, which is generally used to describe a formal design process. In emergency situations the task of the operator is to design a suitable...... control strategy for systems recovery, and the control systems designer should provide a man-machine interface, supporting the operator in identification of his task and in communication with the system at the level of abstraction corresponding to the immediate control requirement. A formalized...

  2. Human Factors Influencing Decision Making

    Science.gov (United States)

    1998-07-01

    Personality and Individual Differences , 21 (1996) pp. 959-969. Ajzen, I. Attitudes, Personality, and Behavior. The Dorsey Press, Chicago...IL, 1988. Alexander, J. R. M. and S. Smales. "Intelligence, learning and long-term memory," Personality and Individual Differences , 23 (1997) pp. 815...intelligence: effects of spatial attention on decision time in high and low IQ subjects," Personality and Individual Differences , 23 (1997) pp.

  3. Decision modeling and acceptance criteria

    DEFF Research Database (Denmark)

    Ditlevsen, Ove Dalager

    2003-01-01

    compensation value of a human life and a public money equivalent of a human life, where the last value usually is considerably larger than the first value, it is possible from the decision analysis to determine an upper limit that the public should impose on the ratio of the owner´s expected loss rate......) that combines wealth in terms of Gross Domestic Product per person, life expectancy at birth, and yearly work time into a single number. The philosophy behind the published evaluations is that the prevention of a loss of a life is counteracted by a cost such that the LQI remains unchanged (Skjong R, Ronold K......; Decision Analysis; Life quality index; Random interest rate; Risk aversion; Socio-economic value; Uncertainty aversion...

  4. Modeling reproductive decisions with simple heuristics

    Directory of Open Access Journals (Sweden)

    Peter Todd

    2013-10-01

    Full Text Available BACKGROUND Many of the reproductive decisions that humans make happen without much planning or forethought, arising instead through the use of simple choice rules or heuristics that involve relatively little information and processing. Nonetheless, these heuristic-guided decisions are typically beneficial, owing to humans' ecological rationality - the evolved fit between our constrained decision mechanisms and the adaptive problems we face. OBJECTIVE This paper reviews research on the ecological rationality of human decision making in the domain of reproduction, showing how fertility-related decisions are commonly made using various simple heuristics matched to the structure of the environment in which they are applied, rather than being made with information-hungry mechanisms based on optimization or rational economic choice. METHODS First, heuristics for sequential mate search are covered; these heuristics determine when to stop the process of mate search by deciding that a good-enough mate who is also mutually interested has been found, using a process of aspiration-level setting and assessing. These models are tested via computer simulation and comparison to demographic age-at-first-marriage data. Next, a heuristic process of feature-based mate comparison and choice is discussed, in which mate choices are determined by a simple process of feature-matching with relaxing standards over time. Parental investment heuristics used to divide resources among offspring are summarized. Finally, methods for testing the use of such mate choice heuristics in a specific population over time are then described.

  5. Studying Collective Human Decision Making and Creativity with Evolutionary Computation.

    Science.gov (United States)

    Sayama, Hiroki; Dionne, Shelley D

    2015-01-01

    We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational, and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making, using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation (EC) in non-traditional ways-(1) as a theoretical framework for reinterpreting the dynamics of idea generation and selection, (2) as a computational simulation model of collective human decision-making processes, and (3) as a research tool for collecting high-resolution experimental data on actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.

  6. MODULAR APPROACH WITH ROUGH DECISION MODELS

    Directory of Open Access Journals (Sweden)

    Ahmed T. Shawky

    2012-09-01

    Full Text Available Decision models which adopt rough set theory have been used effectively in many real world applications.However, rough decision models suffer the high computational complexity when dealing with datasets ofhuge size. In this research we propose a new rough decision model that allows making decisions based onmodularity mechanism. According to the proposed approach, large-size datasets can be divided intoarbitrary moderate-size datasets, then a group of rough decision models can be built as separate decisionmodules. The overall model decision is computed as the consensus decision of all decision modulesthrough some aggregation technique. This approach provides a flexible and a quick way for extractingdecision rules of large size information tables using rough decision models.

  7. Modular Approach with Rough Decision Models

    Directory of Open Access Journals (Sweden)

    Ahmed T. Shawky

    2012-10-01

    Full Text Available Decision models which adopt rough set theory have been used effectively in many real world applications.However, rough decision models suffer the high computational complexity when dealing with datasets ofhuge size. In this research we propose a new rough decision model that allows making decisions based onmodularity mechanism. According to the proposed approach, large-size datasets can be divided intoarbitrary moderate-size datasets, then a group of rough decision models can be built as separate decisionmodules. The overall model decision is computed as the consensus decision of all decision modulesthrough some aggregation technique. This approach provides a flexible and a quick way for extractingdecision rules of large size information tables using rough decision models.

  8. Fire behavior modeling-a decision tool

    Science.gov (United States)

    Jack Cohen; Bill Bradshaw

    1986-01-01

    The usefulness of an analytical model as a fire management decision tool is determined by the correspondence of its descriptive capability to the specific decision context. Fire managers must determine the usefulness of fire models as a decision tool when applied to varied situations. Because the wildland fire phenomenon is complex, analytical fire spread models will...

  9. Towards Human–Robot Teams : Model-Based Analysis of Human Decision Making in Two-Alternative Choice Tasks With Social Feedback

    NARCIS (Netherlands)

    Stewart, Andrew; Cao, Ming; Nedic, Andrea; Tomlin, Damon; Ehrich Leonard, Naomi

    2012-01-01

    With a principled methodology for systematic design of human–robot decision-making teams as a motivating goal, we seek an analytic, model-based description of the influence of team and network design parameters on decision-making performance. Given that there are few reliably predictive models of hu

  10. Optimising Transport Decision Making using Customised Decision Models and Decision Conferences

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn

    The subject of this Ph.D. thesis entitled “Optimising Transport Decision Making using Customised Decision Models and Decision Conferences” is multi-criteria decision analysis (MCDA) and decision support in the context of transport infrastructure assessments. Despite the fact that large amounts...... is concerned with the insufficiency of conventional cost-benefit analysis (CBA), and proposes the use of MCDA as a supplementing tool in order to also capture impacts of a more strategic character in the appraisals and hence make more use of the often large efforts put in the preliminary examinations. MCDA...... identification to the possible decision making. The process makes use of a preliminary problem structuring phase, and an intervention phase featuring the concept of a decision conference where decision-makers and multiple stakeholders have the possibility of interacting with the decision support model...

  11. VIC–CropSyst-v2: A regional-scale modeling platform to simulate the nexus of climate, hydrology, cropping systems, and human decisions

    Directory of Open Access Journals (Sweden)

    K. Malek

    2017-08-01

    Full Text Available Food supply is affected by a complex nexus of land, atmosphere, and human processes, including short- and long-term stressors (e.g., drought and climate change, respectively. A simulation platform that captures these complex elements can be used to inform policy and best management practices to promote sustainable agriculture. We have developed a tightly coupled framework using the macroscale variable infiltration capacity (VIC hydrologic model and the CropSyst agricultural model. A mechanistic irrigation module was also developed for inclusion in this framework. Because VIC–CropSyst combines two widely used and mechanistic models (for crop phenology, growth, management, and macroscale hydrology, it can provide realistic and hydrologically consistent simulations of water availability, crop water requirements for irrigation, and agricultural productivity for both irrigated and dryland systems. This allows VIC–CropSyst to provide managers and decision makers with reliable information on regional water stresses and their impacts on food production. Additionally, VIC–CropSyst is being used in conjunction with socioeconomic models, river system models, and atmospheric models to simulate feedback processes between regional water availability, agricultural water management decisions, and land–atmosphere interactions. The performance of VIC–CropSyst was evaluated on both regional (over the US Pacific Northwest and point scales. Point-scale evaluation involved using two flux tower sites located in agricultural fields in the US (Nebraska and Illinois. The agreement between recorded and simulated evapotranspiration (ET, applied irrigation water, soil moisture, leaf area index (LAI, and yield indicated that, although the model is intended to work on regional scales, it also captures field-scale processes in agricultural areas.

  12. VIC-CropSyst-v2: A regional-scale modeling platform to simulate the nexus of climate, hydrology, cropping systems, and human decisions

    Science.gov (United States)

    Malek, Keyvan; Stöckle, Claudio; Chinnayakanahalli, Kiran; Nelson, Roger; Liu, Mingliang; Rajagopalan, Kirti; Barik, Muhammad; Adam, Jennifer C.

    2017-08-01

    Food supply is affected by a complex nexus of land, atmosphere, and human processes, including short- and long-term stressors (e.g., drought and climate change, respectively). A simulation platform that captures these complex elements can be used to inform policy and best management practices to promote sustainable agriculture. We have developed a tightly coupled framework using the macroscale variable infiltration capacity (VIC) hydrologic model and the CropSyst agricultural model. A mechanistic irrigation module was also developed for inclusion in this framework. Because VIC-CropSyst combines two widely used and mechanistic models (for crop phenology, growth, management, and macroscale hydrology), it can provide realistic and hydrologically consistent simulations of water availability, crop water requirements for irrigation, and agricultural productivity for both irrigated and dryland systems. This allows VIC-CropSyst to provide managers and decision makers with reliable information on regional water stresses and their impacts on food production. Additionally, VIC-CropSyst is being used in conjunction with socioeconomic models, river system models, and atmospheric models to simulate feedback processes between regional water availability, agricultural water management decisions, and land-atmosphere interactions. The performance of VIC-CropSyst was evaluated on both regional (over the US Pacific Northwest) and point scales. Point-scale evaluation involved using two flux tower sites located in agricultural fields in the US (Nebraska and Illinois). The agreement between recorded and simulated evapotranspiration (ET), applied irrigation water, soil moisture, leaf area index (LAI), and yield indicated that, although the model is intended to work on regional scales, it also captures field-scale processes in agricultural areas.

  13. Accommodating complexity and human behaviors in decision analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan; Strip, David R.; Hirsch, Gary B.; Bastian, Mark S.; Braithwaite, Karl R.; Homer, Jack [Homer Consulting

    2007-11-01

    This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

  14. A Subjective Assessment of Alternative Mission Architecture Operations Concepts for the Human Exploration of Mars at NASA Using a Three-Dimensional Multi-Criteria Decision Making Model

    Science.gov (United States)

    Tavana, Madjid

    2003-01-01

    The primary driver for developing missions to send humans to other planets is to generate significant scientific return. NASA plans human planetary explorations with an acceptable level of risk consistent with other manned operations. Space exploration risks can not be completely eliminated. Therefore, an acceptable level of cost, technical, safety, schedule, and political risks and benefits must be established for exploratory missions. This study uses a three-dimensional multi-criteria decision making model to identify the risks and benefits associated with three alternative mission architecture operations concepts for the human exploration of Mars identified by the Mission Operations Directorate at Johnson Space Center. The three alternatives considered in this study include split, combo lander, and dual scenarios. The model considers the seven phases of the mission including: 1) Earth Vicinity/Departure; 2) Mars Transfer; 3) Mars Arrival; 4) Planetary Surface; 5) Mars Vicinity/Departure; 6) Earth Transfer; and 7) Earth Arrival. Analytic Hierarchy Process (AHP) and subjective probability estimation are used to captures the experts belief concerning the risks and benefits of the three alternative scenarios through a series of sequential, rational, and analytical processes.

  15. Human Decision Processes: Implications for SSA Support Tools

    Science.gov (United States)

    Picciano, P.

    2013-09-01

    Despite significant advances in computing power and artificial intelligence (AI), few critical decisions are made without a human decision maker in the loop. Space Situational Awareness (SSA) missions are both critical and complex, typically adhering to the human-in-the-loop (HITL) model. The collection of human operators injects a needed diversity of expert knowledge, experience, and authority required to successfully fulfill SSA tasking. A wealth of literature on human decision making exists citing myriad empirical studies and offering a varied set of prescriptive and descriptive models of judgment and decision making (Hastie & Dawes, 2001; Baron, 2000). Many findings have been proven sufficiently robust to allow information architects or system/interface designers to take action to improve decision processes. For the purpose of discussion, these concepts are bifurcated in two groups: 1) vulnerabilities to mitigate, and 2) capabilities to augment. These vulnerabilities and capabilities refer specifically to the decision process and should not be confused with a shortcoming or skill of a specific human operator. Thus the framing of questions and orders, the automated tools with which to collaborate, priming and contextual data, and the delivery of information all play a critical role in human judgment and choice. Evaluating the merits of any decision can be elusive; in order to constrain this discussion, ‘rational choice' will tend toward the economic model characteristics such as maximizing utility and selection consistency (e.g., if A preferred to B, and B preferred to C, than A should be preferred to C). Simple decision models often encourage one to list the pros and cons of a decision, perhaps use a weighting schema, but one way or another weigh the future benefit (or harm) of making a selection. The result (sought by the rationalist models) should drive toward higher utility. Despite notable differences in researchers' theses (to be discussed in the full

  16. The KONVERGENCE Model for Sustainable Decisions

    Energy Technology Data Exchange (ETDEWEB)

    Kerr, Thomas A; Dakins, Maxine; Gibson, Patrick Lavern; Joe, Jeffrey Clark; Nitschke, Robert Leon; Piet, Steven James

    2002-08-01

    The KONVERGENCE Model for Sustainable Decisions is a new way of viewing, developing, organizing, and evaluating alternatives for decisions that may affect a wide range of interests and that must factor in long timeframes, enduring hazards, and/or continuing responsibilities. It differs from other models in that it addresses the need for decisions to continue to "work" over long time periods in an ever-changing decision environment. The authors show that the model contains three major universes - knowledge, values, and resources (the K, V, and R in KONVERGENCE)- that interact and overlap throughout the effective lifetime of a decision. They discuss how decision-makers and decision participants can use the model to craft and analyze decisions and decision processes that stand the test of time. The authors use the U.S. moon-landing program as an example of a major decision process that was sustained over time. They use the model to explain why events unfolded in the way that they did - and why we are where we are today in that program. The authors believe that this model will be especially useful in long-term decision processes such as those that address contamination cleanup programs, long-term environmental stewardship, and the initial siting of facilities with long-term objectives. Companion papers describe the KONVERGENCE Model process steps and implications for intractable cleanup decisions.

  17. Structure learning in human sequential decision-making.

    Science.gov (United States)

    Acuña, Daniel E; Schrater, Paul

    2010-12-02

    Studies of sequential decision-making in humans frequently find suboptimal performance relative to an ideal actor that has perfect knowledge of the model of how rewards and events are generated in the environment. Rather than being suboptimal, we argue that the learning problem humans face is more complex, in that it also involves learning the structure of reward generation in the environment. We formulate the problem of structure learning in sequential decision tasks using Bayesian reinforcement learning, and show that learning the generative model for rewards qualitatively changes the behavior of an optimal learning agent. To test whether people exhibit structure learning, we performed experiments involving a mixture of one-armed and two-armed bandit reward models, where structure learning produces many of the qualitative behaviors deemed suboptimal in previous studies. Our results demonstrate humans can perform structure learning in a near-optimal manner.

  18. Structure learning in human sequential decision-making.

    Directory of Open Access Journals (Sweden)

    Daniel E Acuña

    Full Text Available Studies of sequential decision-making in humans frequently find suboptimal performance relative to an ideal actor that has perfect knowledge of the model of how rewards and events are generated in the environment. Rather than being suboptimal, we argue that the learning problem humans face is more complex, in that it also involves learning the structure of reward generation in the environment. We formulate the problem of structure learning in sequential decision tasks using Bayesian reinforcement learning, and show that learning the generative model for rewards qualitatively changes the behavior of an optimal learning agent. To test whether people exhibit structure learning, we performed experiments involving a mixture of one-armed and two-armed bandit reward models, where structure learning produces many of the qualitative behaviors deemed suboptimal in previous studies. Our results demonstrate humans can perform structure learning in a near-optimal manner.

  19. Metabolic state alters economic decision making under risk in humans.

    Directory of Open Access Journals (Sweden)

    Mkael Symmonds

    Full Text Available BACKGROUND: Animals' attitudes to risk are profoundly influenced by metabolic state (hunger and baseline energy stores. Specifically, animals often express a preference for risky (more variable food sources when below a metabolic reference point (hungry, and safe (less variable food sources when sated. Circulating hormones report the status of energy reserves and acute nutrient intake to widespread targets in the central nervous system that regulate feeding behaviour, including brain regions strongly implicated in risk and reward based decision-making in humans. Despite this, physiological influences per se have not been considered previously to influence economic decisions in humans. We hypothesised that baseline metabolic reserves and alterations in metabolic state would systematically modulate decision-making and financial risk-taking in humans. METHODOLOGY/PRINCIPAL FINDINGS: We used a controlled feeding manipulation and assayed decision-making preferences across different metabolic states following a meal. To elicit risk-preference, we presented a sequence of 200 paired lotteries, subjects' task being to select their preferred option from each pair. We also measured prandial suppression of circulating acyl-ghrelin (a centrally-acting orexigenic hormone signalling acute nutrient intake, and circulating leptin levels (providing an assay of energy reserves. We show both immediate and delayed effects on risky decision-making following a meal, and that these changes correlate with an individual's baseline leptin and changes in acyl-ghrelin levels respectively. CONCLUSIONS/SIGNIFICANCE: We show that human risk preferences are exquisitely sensitive to current metabolic state, in a direction consistent with ecological models of feeding behaviour but not predicted by normative economic theory. These substantive effects of state changes on economic decisions perhaps reflect shared evolutionarily conserved neurobiological mechanisms. We suggest that

  20. Evolution of quantum-like modeling in decision making processes

    Science.gov (United States)

    Khrennikova, Polina

    2012-12-01

    The application of the mathematical formalism of quantum mechanics to model behavioral patterns in social science and economics is a novel and constantly emerging field. The aim of the so called 'quantum like' models is to model the decision making processes in a macroscopic setting, capturing the particular 'context' in which the decisions are taken. Several subsequent empirical findings proved that when making a decision people tend to violate the axioms of expected utility theory and Savage's Sure Thing principle, thus violating the law of total probability. A quantum probability formula was devised to describe more accurately the decision making processes. A next step in the development of QL-modeling in decision making was the application of Schrödinger equation to describe the evolution of people's mental states. A shortcoming of Schrödinger equation is its inability to capture dynamics of an open system; the brain of the decision maker can be regarded as such, actively interacting with the external environment. Recently the master equation, by which quantum physics describes the process of decoherence as the result of interaction of the mental state with the environmental 'bath', was introduced for modeling the human decision making. The external environment and memory can be referred to as a complex 'context' influencing the final decision outcomes. The master equation can be considered as a pioneering and promising apparatus for modeling the dynamics of decision making in different contexts.

  1. Use of Statechart Assertions for Modeling Human-in-the-Loop Security Analysis and Decision-Making Processes

    Science.gov (United States)

    2012-06-01

    THIS PAGE INTENTIONALLY LEFT BLANK xv LIST OF ACRONYMS AND ABBREVIATIONS BPM Business Process Model BPMN Business Process Modeling Notation C&A...checking leads to an improvement in the quality and success of enterprise software development. Business Process Modeling Notation ( BPMN ) is an...emerging standard that allows business processes to be captured in a standardized format. BPMN lacks formal semantics which leaves many of its features

  2. Modeling Adversaries in Counterterrorism Decisions Using Prospect Theory.

    Science.gov (United States)

    Merrick, Jason R W; Leclerc, Philip

    2016-04-01

    Counterterrorism decisions have been an intense area of research in recent years. Both decision analysis and game theory have been used to model such decisions, and more recently approaches have been developed that combine the techniques of the two disciplines. However, each of these approaches assumes that the attacker is maximizing its utility. Experimental research shows that human beings do not make decisions by maximizing expected utility without aid, but instead deviate in specific ways such as loss aversion or likelihood insensitivity. In this article, we modify existing methods for counterterrorism decisions. We keep expected utility as the defender's paradigm to seek for the rational decision, but we use prospect theory to solve for the attacker's decision to descriptively model the attacker's loss aversion and likelihood insensitivity. We study the effects of this approach in a critical decision, whether to screen containers entering the United States for radioactive materials. We find that the defender's optimal decision is sensitive to the attacker's levels of loss aversion and likelihood insensitivity, meaning that understanding such descriptive decision effects is important in making such decisions.

  3. Using Modularity with Rough Decision Models

    Directory of Open Access Journals (Sweden)

    Ahmed T. Shawky

    2012-01-01

    Full Text Available Many real world applications need to deal with imprecise data. Therefore, there is a need for new techniques which can manage such imprecision. Computational Intelligence (CI techniques are the most appropriate for dealing with imprecise data to help decision makers. It is well known that soft computing techniques like genetic algorithms, neural networks, and fuzzy logic are effective in dealing with problems without explicit model and characterized by uncertainties Using fuzzy set theory considered as major techniques, which allows decision makers to take a good decision using imprecise inexact data and knowledge. Now using rough set is getting quite necessary to be used for its ability to mining such type of data. In this research, we are looking forward to propose a novel technique, which depends on the integration between fuzzy set concepts and rough set theory in mining relational databases. The proposed model allows introducing modularity mechanism, by building a virtual modular decision tables according to variety of decision makers points of view. And introduce decision grouping mechanism for getting the optimizing decision. This approach provides flexibility in decision making verifies all decision standards and determines decision requirements, through modularizing rough decision table, extraction of rough association rules and developing mechanisms for decision grouping.

  4. Human Decisions: Nitrogen Footprints and Environmental Effects

    Science.gov (United States)

    Leach, A. M.; Bleeker, A.; Galloway, J. N.; Erisman, J.

    2012-12-01

    Human consumption choices are responsible for growing losses of reactive nitrogen (Nr) to the environment. Once in the environment, Nr can cause a cascade of negative impacts such as smog, acid rain, coastal eutrophication, climate change, and biodiversity loss. Although all humans must consume nitrogen as protein, the food production process releases substantial Nr to the environment. This dilemma presents a challenge: how do we feed a growing population while reducing Nr? Although top-down strategies to reduce Nr losses (e.g., emissions controls) are necessary, the bottom-up strategies focusing on personal consumption patterns will be imperative to solve the nitrogen challenge. Understanding the effects of different personal choices on Nr losses and the environment is an important first step for this strategy. This paper will utilize information and results from the N-Calculator, a per capita nitrogen footprint model (www.N-Print.org), to analyze the impact of different food consumption patterns on a personal food nitrogen footprint and the environment. Scenarios will analyze the impact of the following dietary patterns on the average United States (28 kg Nr/cap/yr) food nitrogen footprint: 1) Consuming only the recommended protein as defined by the WHO and the USDA; 2) Reducing food waste by 50%; 3) Consuming a vegetarian diet; 4) Consuming a vegan diet; 5) Consuming a demitarian diet (replacing half of animal protein consumption with vegetable protein); 6) Substituting chicken (a more efficient animal protein) with beef (a less efficient animal protein); 7) Consuming sustainably-produced food; and 8) Using advanced wastewater treatment. Preliminary results suggest that widespread advanced wastewater treatment with nutrient removal technology and halving food waste would each reduce the US personal food nitrogen footprint by 13%. In addition, reducing protein consumption to the recommended levels would reduce the footprint by about 42%. Combining these measures

  5. Human-Computer Interactions and Decision Behavior

    Science.gov (United States)

    1984-01-01

    software interfaces. The major components of the reseach program included the Diaiogue Management System. (DMS) operating environment, the role of...specification; and new methods for modeling, designing, and developing human-computer interfaces based on syntactic and semantic specification. The DMS...achieving communication is language. Accordingly, the transaction model employs a linguistic model consisting of parts that relate computer responses

  6. Modeling Based Decision Support Environment Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...

  7. Selection and inhibition mechanisms for human voluntary action decisions.

    Science.gov (United States)

    Zhang, Jiaxiang; Hughes, Laura E; Rowe, James B

    2012-10-15

    One can choose between action alternatives that have no apparent difference in their outcomes. Such voluntary action decisions are associated with widespread frontal-parietal activation, and a tendency to inhibit the repetition of a previous action. However, the mechanism of initiating voluntary actions and the functions of different brain regions during this process remains largely unknown. Here, we combine computational modeling and functional magnetic resonance imaging to test the selection and inhibition mechanisms that mediate trial-to-trial voluntary action decisions. We fitted an optimized accumulator model to behavioral responses in a finger-tapping task in which participants were instructed to make chosen actions or specified actions. Model parameters derived from each individual were then applied to estimate the expected accumulated metabolic activity (EAA) engaged in every single trial. The EAA was associated with blood oxygenation level-dependent responses in a decision work that was maximal in the supplementary motor area and the caudal anterior cingulate cortex, consistent with a competitive accumulation-to-threshold mechanism for action decision by these regions. Furthermore, specific inhibition of the previous action's accumulator was related to the suppression of response repetition. This action-specific inhibition correlated with the activity of the right inferior frontal gyrus, when the option to repeat existed. Our findings suggest that human voluntary action decisions are mediated by complementary processes of intentional selection and inhibition.

  8. USING MODULARITY WITH ROUGH DECISION MODELS

    Directory of Open Access Journals (Sweden)

    Ahmed T. Shawky

    2012-02-01

    Full Text Available Many real world applications need to deal with imprecise data. Therefore, there is a need for newtechniques which can manage such imprecision. Computational Intelligence (CI techniques are the mostappropriate for dealing with imprecise data to help decision makers. It is well known that soft computingtechniques like genetic algorithms, neural networks, and fuzzy logic are effective in dealing with problemswithout explicit model and characterized by uncertainties Using fuzzy set theory considered as majortechniques, which allows decision makers to take a good decision using imprecise inexact data andknowledge. Now using rough set is getting quite necessary to be used for its ability to mining such type ofdata. In this research, we are looking forward to propose a novel technique, which depends on theintegration between fuzzy set concepts and rough set theory in mining relational databases. The proposedmodel allows introducing modularity mechanism, by building a virtual modular decision tables accordingto variety of decision makers points of view. And introduce decision grouping mechanism for getting theoptimizing decision. This approach provides flexibility in decision making verifies all decision standardsand determines decision requirements, through modularizing rough decision table, extraction of roughassociation rules and developing mechanisms for decision grouping.

  9. Optimization-based Analysis and Training of Human Decision Making

    OpenAIRE

    Engelhart, Michael

    2015-01-01

    In the research domain Complex Problem Solving (CPS) in psychology, computer-supported tests are used to analyze complex human decision making and problem solving. The approach is to use computer-based microworlds and to evaluate the performance of participants in such test-scenarios and correlate it to certain characteristics. However, these test-scenarios have usually been defined on a trial-and-error basis, until certain characteristics became apparent. The more complex models ...

  10. Measuring and Modeling Behavioral Decision Dynamics in Collective Evacuation

    CERN Document Server

    Carlson, Jean M; Stromberg, Sean P; Bassett, Danielle S; Craparo, Emily M; Gutierrez-Villarreal, Francisco; Otani, Thomas

    2013-01-01

    Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In each scenario, individuals are faced with a forced "go" versus "no go" evacuation decision, based on information available on competing broadcast and peer-to-peer sources. In this controlled setting, all actions and observations are recorded prior to the decision, enabling development of a quantitative decision making model that accounts for the disaster likelihood, severity, and temporal urgency, as well as competition between networked individuals for limited emergency resources. Individual differences in behavior within this social setting are correlated with individual differences in inh...

  11. A neural model of decision making

    OpenAIRE

    Larsen, Torben

    2008-01-01

    Background: A descriptive neuroeconomic model is aimed for relativity of the concept of economic man to empirical science.Method: A 4-level client-server-integrator model integrating the brain models of McLean and Luria is the general framework for the model of empirical findings.Results: Decision making relies on integration across brain levels of emotional intelligence (LU) and logico-matematico intelligence (RIA), respectively. The integrated decision making formula approaching zero by bot...

  12. A neural model of decision making

    OpenAIRE

    Larsen, Torben

    2008-01-01

    Background: A descriptive neuroeconomic model is aimed for relativity of the concept of economic man to empirical science.Method: A 4-level client-server-integrator model integrating the brain models of McLean and Luria is the general framework for the model of empirical findings.Results: Decision making relies on integration across brain levels of emotional intelligence (LU) and logico-matematico intelligence (RIA), respectively. The integrated decision making formula approaching zero by bot...

  13. Measuring and modeling behavioral decision dynamics in collective evacuation.

    Directory of Open Access Journals (Sweden)

    Jean M Carlson

    Full Text Available Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In a controlled laboratory setting, our results quantify several key factors influencing individual evacuation decision making in a controlled laboratory setting. The experiment includes tensions between broadcast and peer-to-peer information, and contrasts the effects of temporal urgency associated with the imminence of the disaster and the effects of limited shelter capacity for evacuees. Based on empirical measurements of the cumulative rate of evacuations as a function of the instantaneous disaster likelihood, we develop a quantitative model for decision making that captures remarkably well the main features of observed collective behavior across many different scenarios. Moreover, this model captures the sensitivity of individual- and population-level decision behaviors to external pressures, and systematic deviations from the model provide meaningful estimates of variability in the collective response. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios, specifically the development and testing of robust strategies for training and control of evacuations that account for human behavior and network topologies.

  14. Decision variables analysis for structured modeling

    Institute of Scientific and Technical Information of China (English)

    潘启树; 赫东波; 张洁; 胡运权

    2002-01-01

    Structured modeling is the most commonly used modeling method, but it is not quite addaptive to significant changes in environmental conditions. Therefore, Decision Variables Analysis(DVA), a new modelling method is proposed to deal with linear programming modeling and changing environments. In variant linear programming , the most complicated relationships are those among decision variables. DVA classifies the decision variables into different levels using different index sets, and divides a model into different elements so that any change can only have its effect on part of the whole model. DVA takes into consideration the complicated relationships among decision variables at different levels, and can therefore sucessfully solve any modeling problem in dramatically changing environments.

  15. Modeling Non-Standard Financial Decision Making

    NARCIS (Netherlands)

    R.J.D. Potter van Loon (Rogier)

    2014-01-01

    markdownabstractThere are clear theoretical predictions on how a rational person should make financial decisions. When real-life choices are made, however, people often deviate from what economic theory prescribes. This thesis investigates the modeling of non-standard financial decision making by an

  16. Intuitionistic preference modeling and interactive decision making

    CERN Document Server

    Xu, Zeshui

    2014-01-01

    This book offers an in-depth and comprehensive introduction to the priority methods of intuitionistic preference relations, the consistency and consensus improving procedures for intuitionistic preference relations, the approaches to group decision making based on intuitionistic preference relations, the approaches and models for interactive decision making with intuitionistic fuzzy information, and the extended results in interval-valued intuitionistic fuzzy environments.

  17. Incorporating BDI Agents into Human-Agent Decision Making Research

    Science.gov (United States)

    Kamphorst, Bart; van Wissen, Arlette; Dignum, Virginia

    Artificial agents, people, institutes and societies all have the ability to make decisions. Decision making as a research area therefore involves a broad spectrum of sciences, ranging from Artificial Intelligence to economics to psychology. The Colored Trails (CT) framework is designed to aid researchers in all fields in examining decision making processes. It is developed both to study interaction between multiple actors (humans or software agents) in a dynamic environment, and to study and model the decision making of these actors. However, agents in the current implementation of CT lack the explanatory power to help understand the reasoning processes involved in decision making. The BDI paradigm that has been proposed in the agent research area to describe rational agents, enables the specification of agents that reason in abstract concepts such as beliefs, goals, plans and events. In this paper, we present CTAPL: an extension to CT that allows BDI software agents that are written in the practical agent programming language 2APL to reason about and interact with a CT environment.

  18. The Role of Mental Models in Dynamic Decision-Making

    Science.gov (United States)

    2009-03-01

    REINE EN DROIT DU CANADA (2009) Défense Nationale Canada Humansystems® Incorporated Mental Models and DDM Page i Abstract The complex and...help to guide human decision-making. He proposes an alternative descriptive model, the Critique , Explore, Compare, Adapt (CECA) Loop. This model is...section). Humansystems® Incorporated Mental Models and DDM Page 45 The Critique phase involves questioning the conceptual model (“how you want it to

  19. Job Aiding/Training Decision Process Model

    Science.gov (United States)

    1992-09-01

    I[ -, . 1’, oo Ii AL-CR-i1992-0004 AD-A256 947lEE = IIEI ifl ll 1l I JOB AIDING/TRAINING DECISION PROCESS MODEL A R M John P. Zenyuh DTIC S Phillip C...March 1990 - April 1990 4. TITLE AND SUBTITLE S. FUNDING NUMBERS C - F33615-86-C-0545 Job Aiding/Training Decision Process Model PE - 62205F PR - 1121 6...Components to Process Model Decision and Selection Points ........... 32 13. Summary of Subject Recommendations for Aiding Approaches

  20. Introduction to Modeling of Buying Decisions

    Directory of Open Access Journals (Sweden)

    O. Gruenwald

    2011-01-01

    Full Text Available Buying decision models of customers to adjust the competitiveness of organizations have been a challenge for marketing disciplines for several generations. This topic has been explored by researchers and academics in past years, and quite an extensive theoretical base exists with a number of approaches for dealing with this challenge.This paper presents some approaches for creating a customer decision model, and provides experimental results from an electronic investigation intended to build the Kano Model; to prove an ability to understand the modeling principle; and to find out the interpretation of the examined demand in a specific market segment involving students of a technical university. The last section of the paper contains a brief introduction to Choice-Based Modeling with Choice-Based Conjoint Analysis (CBC, which was tailored for modeling purchasing decisions.

  1. Marketing data, models and decisions

    NARCIS (Netherlands)

    Wedel, M; Kamakura, W; Bockenholt, U

    2000-01-01

    Our comments about the paper by Leeflang and Wittink [Internat. J. Res. Marketing, 17 (2000) 105] comprise of two components: first, we address two issues on which we disagree with Leeflang and Wittink: soft versus hard data, and individual-level versus segment-level models. Secondly, we supplement

  2. Towards better modelling and decision support

    DEFF Research Database (Denmark)

    Meli, Mattia; Grimm, V; Augusiak, J.

    2014-01-01

    The potential of ecological models for supporting environmental decision making is increasingly acknowledged. However, it often remains unclear whether a model is realistic and reliable enough. Good practice for developing and testing ecological models has not yet been established. Therefore, TRACE......, thereby also linking modellers and model users, for example stakeholders, decision makers, and developers of policies. We report on first experiences in producing TRACE documents. We found that the original idea underlying TRACE was valid, but to make its use more coherent and efficient, an update of its......, a general framework for documenting a model's rationale, design, and testing was recently suggested. Originally TRACE was aimed at documenting good modelling practice. However, the word 'documentation' does not convey TRACE's urgency. Therefore, we re-define TRACE as a tool for planning, performing...

  3. Towards better modelling and decision support

    DEFF Research Database (Denmark)

    Meli, Mattia; Grimm, V; Augusiak, J.;

    2014-01-01

    The potential of ecological models for supporting environmental decision making is increasingly acknowledged. However, it often remains unclear whether a model is realistic and reliable enough. Good practice for developing and testing ecological models has not yet been established. Therefore, TRACE......, thereby also linking modellers and model users, for example stakeholders, decision makers, and developers of policies. We report on first experiences in producing TRACE documents. We found that the original idea underlying TRACE was valid, but to make its use more coherent and efficient, an update of its......, a general framework for documenting a model's rationale, design, and testing was recently suggested. Originally TRACE was aimed at documenting good modelling practice. However, the word 'documentation' does not convey TRACE's urgency. Therefore, we re-define TRACE as a tool for planning, performing...

  4. Enterprise resource planning implementation decision & optimization models

    Institute of Scientific and Technical Information of China (English)

    Wang Shaojun; Wang Gang; Lü Min; Gao Guoan

    2008-01-01

    To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning (ERP) implementation, combined with program evaluation and review technique (PERT), some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm (GA) based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.

  5. An Integrated Model for Optimization Oriented Decision Aiding and Rule Based Decision Making in Fuzzy Environment

    Directory of Open Access Journals (Sweden)

    A. Yousefli

    2014-01-01

    Full Text Available In this paper a fuzzy decision aid system is developed base on new concepts that presented in the field of fuzzy decision making in fuzzy environment (FDMFE. This framework aids decision makers to understand different circumstances of an uncertain problem that may occur in the future. Also, to keep decision maker from the optimization problem complexities, a decision support system, which can be replaced by optimization problem, is presented to make optimum or near optimum decisions without solving optimization problem directly. An application of the developed decision aid model and the decision support system is presented in the field of inventory models.

  6. A computer-human interaction model to improve the diagnostic accuracy and clinical decision-making during 12-lead electrocardiogram interpretation.

    Science.gov (United States)

    Cairns, Andrew W; Bond, Raymond R; Finlay, Dewar D; Breen, Cathal; Guldenring, Daniel; Gaffney, Robert; Gallagher, Anthony G; Peace, Aaron J; Henn, Pat

    2016-12-01

    The 12-lead Electrocardiogram (ECG) presents a plethora of information and demands extensive knowledge and a high cognitive workload to interpret. Whilst the ECG is an important clinical tool, it is frequently incorrectly interpreted. Even expert clinicians are known to impulsively provide a diagnosis based on their first impression and often miss co-abnormalities. Given it is widely reported that there is a lack of competency in ECG interpretation, it is imperative to optimise the interpretation process. Predominantly the ECG interpretation process remains a paper based approach and whilst computer algorithms are used to assist interpreters by providing printed computerised diagnoses, there are a lack of interactive human-computer interfaces to guide and assist the interpreter. An interactive computing system was developed to guide the decision making process of a clinician when interpreting the ECG. The system decomposes the interpretation process into a series of interactive sub-tasks and encourages the clinician to systematically interpret the ECG. We have named this model 'Interactive Progressive based Interpretation' (IPI) as the user cannot 'progress' unless they complete each sub-task. Using this model, the ECG is segmented into five parts and presented over five user interfaces (1: Rhythm interpretation, 2: Interpretation of the P-wave morphology, 3: Limb lead interpretation, 4: QRS morphology interpretation with chest lead and rhythm strip presentation and 5: Final review of 12-lead ECG). The IPI model was implemented using emerging web technologies (i.e. HTML5, CSS3, AJAX, PHP and MySQL). It was hypothesised that this system would reduce the number of interpretation errors and increase diagnostic accuracy in ECG interpreters. To test this, we compared the diagnostic accuracy of clinicians when they used the standard approach (control cohort) with clinicians who interpreted the same ECGs using the IPI approach (IPI cohort). For the control cohort, the

  7. Studying Collective Human Decision Making and Creativity with Evolutionary Computation

    OpenAIRE

    Sayama, Hiroki; Dionne, Shelley D.

    2014-01-01

    We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and...

  8. This is the Anthropocene, and we're not just input files anymore: coupling urban Human and Earth Systems models for decision support

    Science.gov (United States)

    Spak, S.

    2016-12-01

    Contemporary urban decision support applications and planetary boundary studies both increasingly demand off-the-shelf Anthrogeoscience models that accurately and comprehensively resolve the ways that specific combined changes in policies, technologies, economies, and populations lead to a wide range of environmental and societal impacts, at increasingly fine spatial and temporal scales. Neither traditional integrated assessment nor local spatial models meet these needs. This presentation synthesizes the 21st century history of one- and two-way coupling of demographic, agent-based, and regional economic and infrastructure models with Earth Systems models to identify the core urban systems processes and environmental couplings required to address these emerging challenges. Case studies from toxic and criteria pollutants and greenhouse gases, aerosol climate forcing, land use change, nutrient fluxes, and freshwater use illustrate the shared core design characteristics for a next generation of coupled urban and regional Anthrogeoscience models. Microsimulation applications in UrbanSim highlight existing capabilities and new development activities required to achieve these coupled model design goals within existing modeling frameworks.

  9. Posterior Probability Matching and Human Perceptual Decision Making.

    Directory of Open Access Journals (Sweden)

    Richard F Murray

    2015-06-01

    Full Text Available Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response being correct, is being used increasingly often in models of perception. However, little is known about whether posterior probability matching is consistent with the vast literature on vision and hearing that has developed within signal detection theory. Here we test posterior probability matching models using two tools from detection theory. First, we examine the models' performance in a two-pass experiment, where each block of trials is presented twice, and we measure the proportion of times that the model gives the same response twice to repeated stimuli. We show that at low performance levels, posterior probability matching models give highly inconsistent responses across repeated presentations of identical trials. We find that practised human observers are more consistent across repeated trials than these models predict, and we find some evidence that less practised observers more consistent as well. Second, we compare the performance of posterior probability matching models on a discrimination task to the performance of a theoretical ideal observer that achieves the best possible performance. We find that posterior probability matching is very inefficient at low-to-moderate performance levels, and that human observers can be more efficient than is ever possible according to posterior probability matching models. These findings support classic signal detection models, and rule out a broad class of posterior probability matching models for expert performance on perceptual tasks that range in complexity from contrast discrimination to symmetry detection. However, our findings leave open the possibility that inexperienced observers may show posterior probability matching behaviour, and our methods

  10. A warehouse design decision model: case study

    OpenAIRE

    Geraldes, Carla A. S. (Ed.); Carvalho, Maria do Sameiro; Pereira, Guilherme

    2008-01-01

    Today’s competitive and volatile market requires flexibility, quality and efficiency from the logistics operations. In this context, warehouses are an important link of the logistic chain and warehouse management plays an important role over customer's service. Throughout this work we analyze a mathematical model aiming to support warehouse management decisions. A case study is used for that purpose and the model jointly identifies product allocation to the functional areas in the warehouse, ...

  11. Posterior Probability Matching and Human Perceptual Decision Making

    Science.gov (United States)

    Murray, Richard F.; Patel, Khushbu; Yee, Alan

    2015-01-01

    Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response being correct, is being used increasingly often in models of perception. However, little is known about whether posterior probability matching is consistent with the vast literature on vision and hearing that has developed within signal detection theory. Here we test posterior probability matching models using two tools from detection theory. First, we examine the models’ performance in a two-pass experiment, where each block of trials is presented twice, and we measure the proportion of times that the model gives the same response twice to repeated stimuli. We show that at low performance levels, posterior probability matching models give highly inconsistent responses across repeated presentations of identical trials. We find that practised human observers are more consistent across repeated trials than these models predict, and we find some evidence that less practised observers more consistent as well. Second, we compare the performance of posterior probability matching models on a discrimination task to the performance of a theoretical ideal observer that achieves the best possible performance. We find that posterior probability matching is very inefficient at low-to-moderate performance levels, and that human observers can be more efficient than is ever possible according to posterior probability matching models. These findings support classic signal detection models, and rule out a broad class of posterior probability matching models for expert performance on perceptual tasks that range in complexity from contrast discrimination to symmetry detection. However, our findings leave open the possibility that inexperienced observers may show posterior probability matching behaviour, and our methods provide new tools

  12. A new decision support model for preanesthetic evaluation.

    Science.gov (United States)

    Sobrie, Olivier; Lazouni, Mohammed El Amine; Mahmoudi, Saïd; Mousseau, Vincent; Pirlot, Marc

    2016-09-01

    The principal challenges in the field of anesthesia and intensive care consist of reducing both anesthetic risks and mortality rate. The ASA score plays an important role in patients' preanesthetic evaluation. In this paper, we propose a methodology to derive simple rules which classify patients in a category of the ASA scale on the basis of their medical characteristics. This diagnosis system is based on MR-Sort, a multiple criteria decision analysis model. The proposed method intends to support two steps in this process. The first is the assignment of an ASA score to the patient; the second concerns the decision to accept-or not-the patient for surgery. In order to learn the model parameters and assess its effectiveness, we use a database containing the parameters of 898 patients who underwent preanesthesia evaluation. The accuracy of the learned models for predicting the ASA score and the decision of accepting the patient for surgery is assessed and proves to be better than that of other machine learning methods. Furthermore, simple decision rules can be explicitly derived from the learned model. These are easily interpretable by doctors, and their consistency with medical knowledge can be checked. The proposed model for assessing the ASA score produces accurate predictions on the basis of the (limited) set of patient attributes in the database available for the tests. Moreover, the learned MR-Sort model allows for easy interpretation by providing human-readable classification rules. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Generative Agents for Player Decision Modeling in Games

    DEFF Research Database (Denmark)

    Holmgård, Christoffer; Liapis, Antonios; Togelius, Julian

    2014-01-01

    This paper presents a method for modeling player decision making through the use of agents as AI-driven personas. The paper argues that artificial agents, as generative player models, have properties that allow them to be used as psyhometrically valid, abstract simulations of a human player...... to or divergence from these. Essentially, at each step the action of the human is compared to what actions a number of reinforcement-learned agents would have taken in the same situation, where each agent is trained using a different reward scheme. Finally, extensions are outlined for adapting the agents...

  14. Decision support system for monitoring environmental-human interactions.

    Science.gov (United States)

    Delavari-Edalat, Farideh; Abdi, M Reza

    2009-06-01

    The specific aim of this study is to investigate popular attitudes toward trees. The paper is involved the understanding of biophilia tendencies with respect to people's views in an urban area. Biophilia is considered as the idea insisting on the dependency of human identity on his relationship with nature. The biophilia fundamental tendencies were explored to establish a biological framework for valuing and affiliating the natural world. Accordingly, the nine tendencies i.e. utilitarian, naturalistic, ecologistic-scientific, aesthetic, symbolic, humanistic, moralistic, dominionistic, and negativistic were investigate to find out how people relate to the nature especially trees. The investigation was based on a quantitative interview which was applied to the public population in the Liverpool urban parks. Data collected from the designed questionnaire was followed by analysis of the data to identify people's attitudes towards trees. The results indicated how important the physical appeal and beauty of trees was for the people and also showed the people's emotional attachments to trees. Furthermore, a decision support model was proposed to evaluate human instincts and preferences in relation to their surrounding areas using the Analytical Hierarchical Process (AHP). The proposed model composed the environmental factors and the biophilia tendencies as the criteria of evaluating environmental-human interactions. A case study was then conducted in Liverpool parks to examine theses interactions. The data gathered was used as the input to the AHP model for the attribute analysis. The AHP model would enable environment managers to compose the relevant information via a link between human feelings about urban trees, and environmental factors for monitoring purposes and performance analysis.

  15. Asset Condition, Information Systems and Decision Models

    CERN Document Server

    Willett, Roger; Brown, Kerry; Mathew, Joseph

    2012-01-01

    Asset Condition, Information Systems and Decision Models, is the second volume of the Engineering Asset Management Review Series. The manuscripts provide examples of implementations of asset information systems as well as some practical applications of condition data for diagnostics and prognostics. The increasing trend is towards prognostics rather than diagnostics, hence the need for assessment and decision models that promote the conversion of condition data into prognostic information to improve life-cycle planning for engineered assets. The research papers included here serve to support the on-going development of Condition Monitoring standards. This volume comprises selected papers from the 1st, 2nd, and 3rd World Congresses on Engineering Asset Management, which were convened under the auspices of ISEAM in collaboration with a number of organisations, including CIEAM Australia, Asset Management Council Australia, BINDT UK, and Chinese Academy of Sciences, Beijing University of Chemical Technology, Chin...

  16. Using Modularity with Rough Decision Models

    OpenAIRE

    Ahmed T. Shawky; Hesham A. Hefny; Ashraf H. Abd-Elwahab

    2012-01-01

    Many real world applications need to deal with imprecise data. Therefore, there is a need for new techniques which can manage such imprecision. Computational Intelligence (CI) techniques are the most appropriate for dealing with imprecise data to help decision makers. It is well known that soft computing techniques like genetic algorithms, neural networks, and fuzzy logic are effective in dealing with problems without explicit model and characterized by uncertainties Using fuzzy s...

  17. Integrating a Decision Management Tool with UML Modeling Tools

    DEFF Research Database (Denmark)

    Könemann, Patrick

    Numerous design decisions are made while developing software systems, which influence the architecture of these systems as well as following decisions. A number of decision management tools already exist for capturing, documenting, and maintaining design decisions, but also for guiding developers...... the development process. In this report, we propose an integration of a decision management and a UML-based modeling tool, based on use cases we distill from a case study: the modeling tool shall show all decisions related to a model and allow its users to extend or update them; the decision management tool shall...... trigger the modeling tool to realize design decisions in the models. We define tool-independent concepts and architecture building blocks supporting these use cases and present how they can be implemented in the IBM Rational Software Modeler and Architectural Decision Knowledge Wiki. This seamless...

  18. Assessment of Groundwater Potential Based on Multicriteria Decision Making Model and Decision Tree Algorithms

    Directory of Open Access Journals (Sweden)

    Huajie Duan

    2016-01-01

    Full Text Available Groundwater plays an important role in global climate change and satisfying human needs. In the study, RS (remote sensing and GIS (geographic information system were utilized to generate five thematic layers, lithology, lineament density, topology, slope, and river density considered as factors influencing the groundwater potential. Then, the multicriteria decision model (MCDM was integrated with C5.0 and CART, respectively, to generate the decision tree with 80 surveyed tube wells divided into four classes on the basis of the yield. To test the precision of the decision tree algorithms, the 10-fold cross validation and kappa coefficient were adopted and the average kappa coefficient for C5.0 and CART was 90.45% and 85.09%, respectively. After applying the decision tree to the whole study area, four classes of groundwater potential zones were demarcated. According to the classification result, the four grades of groundwater potential zones, “very good,” “good,” “moderate,” and “poor,” occupy 4.61%, 8.58%, 26.59%, and 60.23%, respectively, with C5.0 algorithm, while occupying the percentages of 4.68%, 10.09%, 26.10%, and 59.13%, respectively, with CART algorithm. Therefore, we can draw the conclusion that C5.0 algorithm is more appropriate than CART for the groundwater potential zone prediction.

  19. Clinical Productivity System - A Decision Support Model

    CERN Document Server

    Bennett, Casey C

    2012-01-01

    Purpose: This goal of this study was to evaluate the effects of a data-driven clinical productivity system that leverages Electronic Health Record (EHR) data to provide productivity decision support functionality in a real-world clinical setting. The system was implemented for a large behavioral health care provider seeing over 75,000 distinct clients a year. Design/methodology/approach: The key metric in this system is a "VPU", which simultaneously optimizes multiple aspects of clinical care. The resulting mathematical value of clinical productivity was hypothesized to tightly link the organization's performance to its expectations and, through transparency and decision support tools at the clinician level, affect significant changes in productivity, quality, and consistency relative to traditional models of clinical productivity. Findings: In only 3 months, every single variable integrated into the VPU system showed significant improvement, including a 30% rise in revenue, 10% rise in clinical percentage, a...

  20. [Mathematical models of decision making and learning].

    Science.gov (United States)

    Ito, Makoto; Doya, Kenji

    2008-07-01

    Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.

  1. Gambling for Gatorade: risk-sensitive decision making for fluid rewards in humans.

    Science.gov (United States)

    Hayden, Benjamin Y; Platt, Michael L

    2009-01-01

    Determining how both humans and animals make decisions in risky situations is a central problem in economics, experimental psychology, behavioral economics, and neurobiology. Typically, humans are risk seeking for gains and risk averse for losses, while animals may display a variety of preferences under risk depending on, amongst other factors, internal state. Such differences in behavior may reflect major cognitive and cultural differences or they may reflect differences in the way risk sensitivity is probed in humans and animals. Notably, in most studies humans make one or a few choices amongst hypothetical or real monetary options, while animals make dozens of repeated choices amongst options offering primary rewards like food or drink. To address this issue, we probed risk-sensitive decision making in human participants using a paradigm modeled on animal studies, in which rewards were either small squirts of Gatorade or small amounts of real money. Possible outcomes and their probabilities were not made explicit in either case. We found that individual patterns of decision making were strikingly similar for both juice and for money, both in overall risk preferences and in trial-to-trial effects of reward outcome on choice. Comparison with decisions made by monkeys for juice in a similar task revealed highly similar gambling styles. These results unite known patterns of risk-sensitive decision making in human and nonhuman primates and suggest that factors such as the way a decision is framed or internal state may underlie observed variation in risk preferences between and within species.

  2. Scalability of human models

    NARCIS (Netherlands)

    Rodarius, C.; Rooij, L. van; Lange, R. de

    2007-01-01

    The objective of this work was to create a scalable human occupant model that allows adaptation of human models with respect to size, weight and several mechanical parameters. Therefore, for the first time two scalable facet human models were developed in MADYMO. First, a scalable human male was

  3. A dataset of human decision-making in teamwork management

    Science.gov (United States)

    Yu, Han; Shen, Zhiqi; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lin, Jun; Cui, Lizhen; Pan, Zhengxiang; Yang, Qiang

    2017-01-01

    Today, most endeavours require teamwork by people with diverse skills and characteristics. In managing teamwork, decisions are often made under uncertainty and resource constraints. The strategies and the effectiveness of the strategies different people adopt to manage teamwork under different situations have not yet been fully explored, partially due to a lack of detailed large-scale data. In this paper, we describe a multi-faceted large-scale dataset to bridge this gap. It is derived from a game simulating complex project management processes. It presents the participants with different conditions in terms of team members' capabilities and task characteristics for them to exhibit their decision-making strategies. The dataset contains detailed data reflecting the decision situations, decision strategies, decision outcomes, and the emotional responses of 1,144 participants from diverse backgrounds. To our knowledge, this is the first dataset simultaneously covering these four facets of decision-making. With repeated measurements, the dataset may help establish baseline variability of decision-making in teamwork management, leading to more realistic decision theoretic models and more effective decision support approaches.

  4. Integrating decision management with UML modeling concepts and tools

    DEFF Research Database (Denmark)

    Könemann, Patrick

    2009-01-01

    to enforce design decisions (modify the models). We define tool-independent concepts and architecture building blocks supporting these requirements and present first ideas how this can be implemented in the IBM Rational Software Modeler and Architectural Decision Knowledge Wiki. This seamless integration......Numerous design decisions including architectural decisions are made while developing a software system, which influence the architecture of the system as well as subsequent decisions. Several tools already exist for managing design decisions, i.e. capturing, documenting, and maintaining them......, but also for guiding the user by proposing subsequent decisions. In model-based software development, many decisions directly affect the structural and behavioral models used to describe and develop a software system and its architecture. However, the decisions are typically not connected to these models...

  5. Reasoning, learning, and creativity: frontal lobe function and human decision-making.

    Science.gov (United States)

    Collins, Anne; Koechlin, Etienne

    2012-01-01

    The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

  6. Reasoning, learning, and creativity: frontal lobe function and human decision-making.

    Directory of Open Access Journals (Sweden)

    Anne Collins

    Full Text Available The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

  7. Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

    Science.gov (United States)

    Collins, Anne; Koechlin, Etienne

    2012-01-01

    The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior. PMID:22479152

  8. Modeling Common-Sense Decisions in Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2010-01-01

    A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

  9. The two-model problem in rational decision making

    NARCIS (Netherlands)

    Boumans, Marcel

    2011-01-01

    A model of a decision problem frames that problem in three dimensions: sample space, target probability and information structure. Each specific model imposes a specific rational decision. As a result, different models may impose different, even contradictory, rational decisions, creating choice ‘an

  10. A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs

    DEFF Research Database (Denmark)

    Pourmoayed, Reza; Nielsen, Lars Relund; Kristensen, Anders Ringgaard

    2016-01-01

    Feeding is the most important cost in the production of growing pigs and has a direct impact on the marketing decisions, growth and the final quality of the meat. In this paper, we address the sequential decision problem of when to change the feed-mix within a finisher pig pen and when to pick pigs...... for marketing. We formulate a hierarchical Markov decision process with three levels representing the decision process. The model considers decisions related to feeding and marketing and finds the optimal decision given the current state of the pen. The state of the system is based on information from on...

  11. Better decision making in complex, dynamic tasks training with human-facilitated interactive learning environments

    CERN Document Server

    Qudrat-Ullah, Hassan

    2015-01-01

    This book describes interactive learning environments (ILEs) and their underlying concepts. It explains how ILEs can be used to improve the decision-making process and how these improvements can be empirically verified. The objective of this book is to enhance our understanding of and to gain insights into the process by which human facilitated ILEs are effectively designed and used in improving users’ decision making in complex, dynamic tasks. This book is divided into four major parts. Part I serves as an introduction to the importance and complexity of decision making in dynamic tasks. Part II provides background material, drawing upon relevant literature, for the development of an integrated process model on the effectiveness of human facilitated ILEs in improving decision making in dynamic tasks. Part III focuses on the design, development, and application of FishBankILE in laboratory experiments to gather empirical evidence for the validity of the process model. Finally, part IV presents a comprehensi...

  12. High Assurance Human-Centric Decision Systems

    Science.gov (United States)

    2013-05-01

    into a formal state machine model [11]. Our synthesis algo- rithm 1) identifies input and output variables from the MSCs; 2) based on the mode class... machine model with a next-state function T : s × e → s′, where s is the current system state, e a single system input (the stimulus), and s′ the new...large. Fig. 3. MSC for operator movement of a UAV’s way point. In our approach, a MSC describes a sequence of stimulus- response behaviors of a state

  13. Statistical Decision-Tree Models for Parsing

    CERN Document Server

    Magerman, D M

    1995-01-01

    Syntactic natural language parsers have shown themselves to be inadequate for processing highly-ambiguous large-vocabulary text, as is evidenced by their poor performance on domains like the Wall Street Journal, and by the movement away from parsing-based approaches to text-processing in general. In this paper, I describe SPATTER, a statistical parser based on decision-tree learning techniques which constructs a complete parse for every sentence and achieves accuracy rates far better than any published result. This work is based on the following premises: (1) grammars are too complex and detailed to develop manually for most interesting domains; (2) parsing models must rely heavily on lexical and contextual information to analyze sentences accurately; and (3) existing {$n$}-gram modeling techniques are inadequate for parsing models. In experiments comparing SPATTER with IBM's computer manuals parser, SPATTER significantly outperforms the grammar-based parser. Evaluating SPATTER against the Penn Treebank Wall ...

  14. Use of Participatory Systems Dynamics Modelling to Generate User-Friendly Decision Support Systems for the Design of Management Policies for Complex Human-Environmental Systems: A Case Study from the Varied Socio-environmental Landscape of Guatemala

    Science.gov (United States)

    Malard, J. J.; Baig, A. I.; Carrera, J.; Mellini, L.; Pineda, P.; Monterroso, O.; Melgar-Quiñonez, H.; Adamowski, J. F.; Halbe, J.; Monardes, H.; Gálvez, J.

    2014-12-01

    The design of effective management policies for socioenvironmental systems requires the development of comprehensive, yet sufficiently simple, decision support systems (DSS) for policy makers. Guatemala is a particularly complex case, combining an enormous diversity of climates, geographies, and agroecosystems within a very small geographical scale. Although food insecurity levels are very high, indicating a generally inadequate management of the varied agroecosystems of the country, different regions have shown vastly different trends in food insecurity over the past decade, including between regions with similar geophysical and climatic characteristics and/or governmental programmes (e.g., agricultural support). These observations suggest two important points: firstly, that not merely environmental conditions but rather socio-environmental interactions play a crucial role in the successful management of human-environmental systems, and, secondly, that differences in the geophysical and climatic environments between the diverse regions significantly impact the success or failure of policies. This research uses participatory systems dynamic modelling (SDM) to build a DSS that allows local decision-makers to (1) determine the impact of current and potential policies on agroecosystem management and food security, and (2) design sustainable and resilient policies for the future. The use of participatory SDM offers several benefits, including the active involvement of the end recipients in the development of the model, greatly increasing its acceptability; the integration of physical (e.g., precipitation, crop yield) and social components in one model; adequacy for modelling long-term trends in response to particular policy decisions; and the inclusion of local stakeholder knowledge on system structure and trends through the participatory process. Preliminary results suggest that there is a set of common variables explaining the generally high levels of food insecurity

  15. Decision models in engineering and management

    CERN Document Server

    2015-01-01

    Providing a comprehensive overview of various methods  and applications in decision engineering, this book presents chapters written by a range experts in the field. It presents conceptual aspects of decision support applications in various areas including finance, vendor selection, construction, process management, water management and energy, agribusiness , production scheduling and control, and waste management. In addition to this, a special focus is given to methods of multi-criteria decision analysis. Decision making in organizations is a recurrent theme and is essential for business continuity.  Managers from various fields including public, private, industrial, trading or service sectors are required to make decisions. Consequently managers need the support of these structured methods in order to engage in effective decision making. This book provides a valuable resource for graduate students, professors and researchers of decision analysis, multi-criteria decision analysis and group decision analys...

  16. Limitations of multimedia models for use in environmental decision making.

    Science.gov (United States)

    Travis, C C; Obenshain, K R; Regens, J L; Whipple, C G

    2001-09-01

    The United States currently is engaged in a complex, multi-billion dollar effort to cleanup a legacy of both privately- and federally-owned hazardous waste sites. Decisions regarding the best approach for remediation of these sites often are based on the analysis of potential risks to human health and the environment. A cornerstone of such analysis is the frequent use of computerized multimedia environmental transport models, to evaluate the large quantities of information necessary to understand the present and future implications of contamination at a site. One barrier to wide-spread use of this analytical procedure is the view that results obtained using computer models are highly dependent on user input, and therefore, subject to manipulation. It is widely recognized that for decisions to be both credible and implementable, the public must have confidence in both the scientific basis for judgments involved and the decision processes employed (NRC, 1983). Our purpose in this article is to overview the difficulties associated with application of multimedia models to real world problems and the contribution these models can make to technically sound estimates of exposure and risk.

  17. Theoretical bases of modeling decision-marketing solutions

    OpenAIRE

    Grigoruk Pavel Mikhaylovych

    2012-01-01

    The paper deals with issues related with theoretical aspects of modelling of marketing decision making process. According to system approach marketing decision making process is seen as a set of related subprocesses. Provided an opportunity to use the economic and mathematical modelling at each stage of the decision making process.

  18. Decision Making, Models of Mind, and the New Cognitive Science.

    Science.gov (United States)

    Evers, Colin W.

    1998-01-01

    Explores implications for understanding educational decision making from a cognitive science perspective. Examines three models of mind providing the methodological framework for decision-making studies. The "absent mind" embodies the behaviorist research tradition. The "functionalist mind" underwrites traditional cognitivism…

  19. Decision Making, Models of Mind, and the New Cognitive Science.

    Science.gov (United States)

    Evers, Colin W.

    1998-01-01

    Explores implications for understanding educational decision making from a cognitive science perspective. Examines three models of mind providing the methodological framework for decision-making studies. The "absent mind" embodies the behaviorist research tradition. The "functionalist mind" underwrites traditional cognitivism…

  20. Agent-Based Modeling of Consumer Decision making Process Based on Power Distance and Personality

    NARCIS (Netherlands)

    Roozmand, O.; Ghasem-Aghaee, N.; Hofstede, G.J.; Nematbakhsh, M.A.; Baraani, A.; Verwaart, T.

    2011-01-01

    Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs.

  1. Agent-Based Modeling of Consumer Decision making Process Based on Power Distance and Personality

    NARCIS (Netherlands)

    Roozmand, O.; Ghasem-Aghaee, N.; Hofstede, G.J.; Nematbakhsh, M.A.; Baraani, A.; Verwaart, T.

    2011-01-01

    Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs.

  2. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-10-01

    Full Text Available An important source of uncertainty in climate models is linked to the calibration of model parameters. Interest in systematic and automated parameter optimization procedures stems from the desire to improve the model climatology and to quantify the average sensitivity associated with potential changes in the climate system. Building upon on the smoothness of the response of an atmospheric circulation model (AGCM to changes of four adjustable parameters, Neelin et al. (2010 used a quadratic metamodel to objectively calibrate the AGCM. The metamodel accurately estimates global spatial averages of common fields of climatic interest, from precipitation, to low and high level winds, from temperature at various levels to sea level pressure and geopotential height, while providing a computationally cheap strategy to explore the influence of parameter settings. Here, guided by the metamodel, the ambiguities or dilemmas related to the decision making process in relation to model sensitivity and optimization are examined. Simulations of current climate are subject to considerable regional-scale biases. Those biases may vary substantially depending on the climate variable considered, and/or on the performance metric adopted. Common dilemmas are associated with model revisions yielding improvement in one field or regional pattern or season, but degradation in another, or improvement in the model climatology but degradation in the interannual variability representation. Challenges are posed to the modeler by the high dimensionality of the model output fields and by the large number of adjustable parameters. The use of the metamodel in the optimization strategy helps visualize trade-offs at a regional level, e.g., how mismatches between sensitivity and error spatial fields yield regional errors under minimization of global objective functions.

  3. High dimensional decision dilemmas in climate models

    Directory of Open Access Journals (Sweden)

    A. Bracco

    2013-05-01

    Full Text Available An important source of uncertainty in climate models is linked to the calibration of model parameters. Interest in systematic and automated parameter optimization procedures stems from the desire to improve the model climatology and to quantify the average sensitivity associated with potential changes in the climate system. Neelin et al. (2010 used a quadratic metamodel to objectively calibrate an atmospheric circulation model (AGCM around four adjustable parameters. The metamodel accurately estimates global spatial averages of common fields of climatic interest, from precipitation, to low and high level winds, from temperature at various levels to sea level pressure and geopotential height, while providing a computationally cheap strategy to explore the influence of parameter settings. Here, guided by the metamodel, the ambiguities or dilemmas related to the decision making process in relation to model sensitivity and optimization are examined. Simulations of current climate are subject to considerable regional-scale biases. Those biases may vary substantially depending on the climate variable considered, and/or on the performance metric adopted. Common dilemmas are associated with model revisions yielding improvement in one field or regional pattern or season, but degradation in another, or improvement in the model climatology but degradation in the interannual variability representation. Challenges are posed to the modeler by the high dimensionality of the model output fields and by the large number of adjustable parameters. The use of the metamodel in the optimization strategy helps visualize trade-offs at a regional level, e.g. how mismatches between sensitivity and error spatial fields yield regional errors under minimization of global objective functions.

  4. [Decision analysis in radiology using Markov models].

    Science.gov (United States)

    Golder, W

    2000-01-01

    Markov models (Multistate transition models) are mathematical tools to simulate a cohort of individuals followed over time to assess the prognosis resulting from different strategies. They are applied on the assumption that persons are in one of a finite number of states of health (Markov states). Each condition is given a transition probability as well as an incremental value. Probabilities may be chosen constant or varying over time due to predefined rules. Time horizon is divided into equal increments (Markov cycles). The model calculates quality-adjusted life expectancy employing real-life units and values and summing up the length of time spent in each health state adjusted for objective outcomes and subjective appraisal. This sort of modeling prognosis for a given patient is analogous to utility in common decision trees. Markov models can be evaluated by matrix algebra, probabilistic cohort simulation and Monte Carlo simulation. They have been applied to assess the relative benefits and risks of a limited number of diagnostic and therapeutic procedures in radiology. More interventions should be submitted to Markov analyses in order to elucidate their cost-effectiveness.

  5. Modeling of Mixed Decision Making Process

    OpenAIRE

    yahia, Nesrine Ben; Bellamine, Narjès; Ghezala, Henda Ben

    2012-01-01

    Decision making whenever and wherever it is happened is key to organizations success. In order to make correct decision, individuals, teams and organizations need both knowledge management (to manage content) and collaboration (to manage group processes) to make that more effective and efficient. In this paper, we explain the knowledge management and collaboration convergence. Then, we propose a formal description of mixed and multimodal decision making (MDM) process where decision may be mad...

  6. Modeling of Mixed Decision Making Process

    OpenAIRE

    Yahia, Nesrine Ben; Bellamine, Narjès; Ghezala, Henda Ben

    2012-01-01

    Decision making whenever and wherever it is happened is key to organizations success. In order to make correct decision, individuals, teams and organizations need both knowledge management (to manage content) and collaboration (to manage group processes) to make that more effective and efficient. In this paper, we explain the knowledge management and collaboration convergence. Then, we propose a formal description of mixed and multimodal decision making (MDM) process where decision may be mad...

  7. Leadership of risk decision making in a complex, technology organization: The deliberative decision making model

    Science.gov (United States)

    Flaming, Susan C.

    2007-12-01

    The continuing saga of satellite technology development is as much a story of successful risk management as of innovative engineering. How do program leaders on complex, technology projects manage high stakes risks that threaten business success and satellite performance? This grounded theory study of risk decision making portrays decision leadership practices at one communication satellite company. Integrated product team (IPT) leaders of multi-million dollar programs were interviewed and observed to develop an extensive description of the leadership skills required to navigate organizational influences and drive challenging risk decisions to closure. Based on the study's findings the researcher proposes a new decision making model, Deliberative Decision Making, to describe the program leaders' cognitive and organizational leadership practices. This Deliberative Model extends the insights of prominent decision making models including the rational (or classical) and the naturalistic and qualifies claims made by bounded rationality theory. The Deliberative Model describes how leaders proactively engage resources to play a variety of decision leadership roles. The Model incorporates six distinct types of leadership decision activities, undertaken in varying sequence based on the challenges posed by specific risks. Novel features of the Deliberative Decision Model include: an inventory of leadership methods for managing task challenges, potential stakeholder bias and debates; four types of leadership meta-decisions that guide decision processes, and aligned organizational culture. Both supporting and constraining organizational influences were observed as leaders managed major risks, requiring active leadership on the most difficult decisions. Although the company's engineering culture emphasized the importance of data-based decisions, the uncertainties intrinsic to satellite risks required expert engineering judgment to be exercised throughout. An investigation into

  8. Modeling decisions information fusion and aggregation operators

    CERN Document Server

    Torra, Vicenc

    2007-01-01

    Information fusion techniques and aggregation operators produce the most comprehensive, specific datum about an entity using data supplied from different sources, thus enabling us to reduce noise, increase accuracy, summarize and extract information, and make decisions. These techniques are applied in fields such as economics, biology and education, while in computer science they are particularly used in fields such as knowledge-based systems, robotics, and data mining. This book covers the underlying science and application issues related to aggregation operators, focusing on tools used in practical applications that involve numerical information. Starting with detailed introductions to information fusion and integration, measurement and probability theory, fuzzy sets, and functional equations, the authors then cover the following topics in detail: synthesis of judgements, fuzzy measures, weighted means and fuzzy integrals, indices and evaluation methods, model selection, and parameter extraction. The method...

  9. The human factor: behavioral and neural correlates of humanized perception in moral decision making.

    Directory of Open Access Journals (Sweden)

    Jasminka Majdandžić

    Full Text Available The extent to which people regard others as full-blown individuals with mental states ("humanization" seems crucial for their prosocial motivation towards them. Previous research has shown that decisions about moral dilemmas in which one person can be sacrificed to save multiple others do not consistently follow utilitarian principles. We hypothesized that this behavior can be explained by the potential victim's perceived humanness and an ensuing increase in vicarious emotions and emotional conflict during decision making. Using fMRI, we assessed neural activity underlying moral decisions that affected fictitious persons that had or had not been experimentally humanized. In implicit priming trials, participants either engaged in mentalizing about these persons (Humanized condition or not (Neutral condition. In subsequent moral dilemmas, participants had to decide about sacrificing these persons' lives in order to save the lives of numerous others. Humanized persons were sacrificed less often, and the activation pattern during decisions about them indicated increased negative affect, emotional conflict, vicarious emotions, and behavioral control (pgACC/mOFC, anterior insula/IFG, aMCC and precuneus/PCC. Besides, we found enhanced effective connectivity between aMCC and anterior insula, which suggests increased emotion regulation during decisions affecting humanized victims. These findings highlight the importance of others' perceived humanness for prosocial behavior - with aversive affect and other-related concern when imagining harming more "human-like" persons acting against purely utilitarian decisions.

  10. Modeling human operator involvement in robotic systems

    NARCIS (Netherlands)

    Wewerinke, P.H.

    1991-01-01

    A modeling approach is presented to describe complex manned robotic systems. The robotic system is modeled as a (highly) nonlinear, possibly time-varying dynamic system including any time delays in terms of optimal estimation, control and decision theory. The role of the human operator(s) is modeled

  11. [Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

    Science.gov (United States)

    Wu, Dehua

    2016-01-01

    The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

  12. Decision models in designing flexible production systems

    Directory of Open Access Journals (Sweden)

    Florescu Adriana

    2017-01-01

    Full Text Available Flexible production system is a complex whole that raise some issues in terms of its design and in relation to the conditions for implementing it. To implement a flexible production system configuration must be found that satisfies both economic and system performance requirements. The configuration which best meet the objectives of introducing a flexible production system must be sought in the set of alternatives defined and evaluated. In this paper we present a methodology of realising the configuration and complex evaluation of the analyzed system. It will be developed models which generate new alternative configurations, optimization and evaluation models of the performance of the flexible production system. This will create a framework for interactive decision support, user-oriented that can be used by management to solve this selection problem. The applicative character of the study consist in tracking of the technological process in real time using the developed software package on the designed system, based on mathematical models for configuration and optimization of the system.

  13. Integrating Design Decision Management with Model-based Software Development

    DEFF Research Database (Denmark)

    Könemann, Patrick

    Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts...... of the system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design decisions is often manual and tedious work on design models. Moreover, keeping design models consistent...

  14. Leadership, consensus decision making and collective behaviour in humans.

    Science.gov (United States)

    Dyer, John R G; Johansson, Anders; Helbing, Dirk; Couzin, Iain D; Krause, Jens

    2009-03-27

    This paper reviews the literature on leadership in vertebrate groups, including recent work on human groups, before presenting the results of three new experiments looking at leadership and decision making in small and large human groups. In experiment 1, we find that both group size and the presence of uninformed individuals can affect the speed with which small human groups (eight people) decide between two opposing directional preferences and the likelihood of the group splitting. In experiment 2, we show that the spatial positioning of informed individuals within small human groups (10 people) can affect the speed and accuracy of group motion. We find that having a mixture of leaders positioned in the centre and on the edge of a group increases the speed and accuracy with which the group reaches their target. In experiment 3, we use large human crowds (100 and 200 people) to demonstrate that the trends observed from earlier work using small human groups can be applied to larger crowds. We find that only a small minority of informed individuals is needed to guide a large uninformed group. These studies build upon important theoretical and empirical work on leadership and decision making in animal groups.

  15. Quantum-Like Bayesian Networks for Modeling Decision Making

    Directory of Open Access Journals (Sweden)

    Catarina eMoreira

    2016-01-01

    Full Text Available In this work, we explore an alternative quantum structure to perform quantum probabilistic inferences to accommodate the paradoxical findings of the Sure Thing Principle. We propose a Quantum-Like Bayesian Network, which consists in replacing classical probabilities by quantum probability amplitudes. However, since this approach suffers from the problem of exponential growth of quantum parameters, we also propose a similarity heuristic that automatically fits quantum parameters through vector similarities. This makes the proposed model general and predictive in contrast to the current state of the art models, which cannot be generalized for more complex decision scenarios and that only provide an explanatory nature for the observed paradoxes. In the end, the model that we propose consists in a nonparametric method for estimating inference effects from a statistical point of view. It is a statistical model that is simpler than the previous quantum dynamic and quantum-like models proposed in the literature. We tested the proposed network with several empirical data from the literature, mainly from the Prisoner's Dilemma game and the Two Stage Gambling game. The results obtained show that the proposed quantum Bayesian Network is a general method that can accommodate violations of the laws of classical probability theory and make accurate predictions regarding human decision-making in these scenarios.

  16. Quantum-Like Bayesian Networks for Modeling Decision Making.

    Science.gov (United States)

    Moreira, Catarina; Wichert, Andreas

    2016-01-01

    In this work, we explore an alternative quantum structure to perform quantum probabilistic inferences to accommodate the paradoxical findings of the Sure Thing Principle. We propose a Quantum-Like Bayesian Network, which consists in replacing classical probabilities by quantum probability amplitudes. However, since this approach suffers from the problem of exponential growth of quantum parameters, we also propose a similarity heuristic that automatically fits quantum parameters through vector similarities. This makes the proposed model general and predictive in contrast to the current state of the art models, which cannot be generalized for more complex decision scenarios and that only provide an explanatory nature for the observed paradoxes. In the end, the model that we propose consists in a nonparametric method for estimating inference effects from a statistical point of view. It is a statistical model that is simpler than the previous quantum dynamic and quantum-like models proposed in the literature. We tested the proposed network with several empirical data from the literature, mainly from the Prisoner's Dilemma game and the Two Stage Gambling game. The results obtained show that the proposed quantum Bayesian Network is a general method that can accommodate violations of the laws of classical probability theory and make accurate predictions regarding human decision-making in these scenarios.

  17. The study of prescriptive and descriptive models of decision making

    Directory of Open Access Journals (Sweden)

    Ashok A Divekar

    2012-04-01

    Full Text Available The field of decision making can be loosely divided into two parts: the study of prescriptive models and the study of descriptive models. Prescriptive decision scientists are concerned with prescribing methods for making optimal decisions. Descriptive decision researchers are concerned with the bounded way in which the decisions are actually made. The statistics courses treat risk from a prescriptive, by suggesting rational methods. This paper brings out the work done by many researchers by examining the psychological factors that explain how managers deviate from rationality in responding to uncertainty.

  18. FUZZY DECISION MAKING MODEL FOR BYZANTINE AGREEMENT

    Directory of Open Access Journals (Sweden)

    S. MURUGAN

    2014-04-01

    Full Text Available Byzantine fault tolerance is of high importance in the distributed computing environment where malicious attacks and software errors are common. A Byzantine process sends arbitrary messages to every other process. An effective fuzzy decision making approach is proposed to eliminate the Byzantine behaviour of the services in the distributed environment. It is proposed to derive a fuzzy decision set in which the alternatives are ranked with grade of membership and based on that an appropriate decision can be arrived on the messages sent by the different services. A balanced decision is to be taken from the messages received across the services. To accomplish this, Hurwicz criterion is used to balance the optimistic and pessimistic views of the decision makers on different services. Grades of membership for the services are assessed using the non-functional Quality of Service parameters and have been estimated using fuzzy entropy measure which logically ranks the participant services. This approach for decision making is tested by varying the number of processes, varying the number of faulty services, varying the message values sent to different services and considering the variation in the views of the decision makers about the services. The experimental result shows that the decision reached is an enhanced one and in case of conflict, the proposed approach provides a concrete result, whereas decision taken using the Lamport’s algorithm is an arbitrary one.

  19. Modelling contractor’s bidding decision

    Directory of Open Access Journals (Sweden)

    Biruk Sławomir

    2017-03-01

    Full Text Available The authors aim to provide a set of tools to facilitate the main stages of the competitive bidding process for construction contractors. These involve 1 deciding whether to bid, 2 calculating the total price, and 3 breaking down the total price into the items of the bill of quantities or the schedule of payments to optimise contractor cash flows. To define factors that affect the decision to bid, the authors rely upon literature on the subject and put forward that multi-criteria methods are applied to calculate a single measure of contract attractiveness (utility value. An attractive contract implies that the contractor is likely to offer a lower price to increase chances of winning the competition. The total bid price is thus to be interpolated between the lowest acceptable and the highest justifiable price based on the contract attractiveness. With the total bid price established, the next step is to split it between the items of the schedule of payments. A linear programming model is proposed for this purpose. The application of the models is illustrated with a numerical example.

  20. Multiview coding mode decision with hybrid optimal stopping model.

    Science.gov (United States)

    Zhao, Tiesong; Kwong, Sam; Wang, Hanli; Wang, Zhou; Pan, Zhaoqing; Kuo, C-C Jay

    2013-04-01

    In a generic decision process, optimal stopping theory aims to achieve a good tradeoff between decision performance and time consumed, with the advantages of theoretical decision-making and predictable decision performance. In this paper, optimal stopping theory is employed to develop an effective hybrid model for the mode decision problem, which aims to theoretically achieve a good tradeoff between the two interrelated measurements in mode decision, as computational complexity reduction and rate-distortion degradation. The proposed hybrid model is implemented and examined with a multiview encoder. To support the model and further promote coding performance, the multiview coding mode characteristics, including predicted mode probability and estimated coding time, are jointly investigated with inter-view correlations. Exhaustive experimental results with a wide range of video resolutions reveal the efficiency and robustness of our method, with high decision accuracy, negligible computational overhead, and almost intact rate-distortion performance compared to the original encoder.

  1. Venture Theory: A Model of Decision Weights.

    Science.gov (United States)

    1988-01-01

    restrictions are important in that nonadditive decision weights can be used to "explain" many anomalies of standard choice theory . Implications. There are...1974). On utility functions. Theory and Decision, 5, 205-242. Chew, S. H., & MacCrimmon, K. R. Alpha-nu choice theory : A generalization of expected

  2. Decision tree modeling with relational views

    CERN Document Server

    Bentayeb, Fadila

    2002-01-01

    Data mining is a useful decision support technique that can be used to discover production rules in warehouses or corporate data. Data mining research has made much effort to apply various mining algorithms efficiently on large databases. However, a serious problem in their practical application is the long processing time of such algorithms. Nowadays, one of the key challenges is to integrate data mining methods within the framework of traditional database systems. Indeed, such implementations can take advantage of the efficiency provided by SQL engines. In this paper, we propose an integrating approach for decision trees within a classical database system. In other words, we try to discover knowledge from relational databases, in the form of production rules, via a procedure embedding SQL queries. The obtained decision tree is defined by successive, related relational views. Each view corresponds to a given population in the underlying decision tree. We selected the classical Induction Decision Tree (ID3) a...

  3. A Survey of Game Theoretic Approaches to Modelling Decision-Making in Information Warfare Scenarios

    Directory of Open Access Journals (Sweden)

    Kathryn Merrick

    2016-07-01

    Full Text Available Our increasing dependence on information technologies and autonomous systems has escalated international concern for information- and cyber-security in the face of politically, socially and religiously motivated cyber-attacks. Information warfare tactics that interfere with the flow of information can challenge the survival of individuals and groups. It is increasingly important that both humans and machines can make decisions that ensure the trustworthiness of information, communication and autonomous systems. Subsequently, an important research direction is concerned with modelling decision-making processes. One approach to this involves modelling decision-making scenarios as games using game theory. This paper presents a survey of information warfare literature, with the purpose of identifying games that model different types of information warfare operations. Our contribution is a systematic identification and classification of information warfare games, as a basis for modelling decision-making by humans and machines in such scenarios. We also present a taxonomy of games that map to information warfare and cyber crime problems as a precursor to future research on decision-making in such scenarios. We identify and discuss open research questions including the role of behavioural game theory in modelling human decision making and the role of machine decision-making in information warfare scenarios.

  4. Clinical inferences and decisions--III. Utility assessment and the Bayesian decision model.

    Science.gov (United States)

    Aspinall, P A; Hill, A R

    1984-01-01

    It is accepted that errors of misclassifications, however small, can occur in clinical decisions but it cannot be assumed that the importance associated with false positive errors is the same as that for false negatives. The relative importance of these two types of error is frequently implied by a decision maker in the different weighting factors or utilities he assigns to the alternative consequences of his decisions. Formal procedures are available by which it is possible to make explicit in numerical form the value or worth of the outcome of a decision process. The two principal methods are described for generating utilities as associated with clinical decisions. The concept and application of utility is then expanded from a unidimensional to a multidimensional problem where, for example, one variable may be state of health and another monetary assets. When combined with the principles of subjective probability and test criterion selection outlined in Parts I and II of this series, the consequent use of utilities completes the framework upon which the general Bayesian model of clinical decision making is based. The five main stages in this general decision making model are described and applications of the model are illustrated with clinical examples from the field of ophthalmology. These include examples for unidimensional and multidimensional problems which are worked through in detail to illustrate both the principles and methodology involved in a rationalized normative model of clinical decision making behaviour.

  5. A Layered Decision Model for Cost-Effective System Security

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Huaqiang; Alves-Foss, James; Soule, Terry; Pforsich, Hugh; Zhang, Du; Frincke, Deborah A.

    2008-10-01

    System security involves decisions in at least three areas: identification of well-defined security policies, selection of cost-effective defence strategies, and implementation of real-time defence tactics. Although choices made in each of these areas affect the others, existing decision models typically handle these three decision areas in isolation. There is no comprehensive tool that can integrate them to provide a single efficient model for safeguarding a network. In addition, there is no clear way to determine which particular combinations of defence decisions result in cost-effective solutions. To address these problems, this paper introduces a Layered Decision Model (LDM) for use in deciding how to address defence decisions based on their cost-effectiveness. To validate the LDM and illustrate how it is used, we used simulation to test model rationality and applied the LDM to the design of system security for an e-commercial business case.

  6. Behavioural modelling of irrigation decision making under water scarcity

    Science.gov (United States)

    Foster, T.; Brozovic, N.; Butler, A. P.

    2013-12-01

    Providing effective policy solutions to aquifer depletion caused by abstraction for irrigation is a key challenge for socio-hydrology. However, most crop production functions used in hydrological models do not capture the intraseasonal nature of irrigation planning, or the importance of well yield in land and water use decisions. Here we develop a method for determining stochastic intraseasonal water use that is based on observed farmer behaviour but is also theoretically consistent with dynamically optimal decision making. We use the model to (i) analyse the joint land and water use decision by farmers; (ii) to assess changes in behaviour and production risk in response to water scarcity; and (iii) to understand the limits of applicability of current methods in policy design. We develop a biophysical model of water-limited crop yield building on the AquaCrop model. The model is calibrated and applied to case studies of irrigated corn production in Nebraska and Texas. We run the model iteratively, using long-term climate records, to define two formulations of the crop-water production function: (i) the aggregate relationship between total seasonal irrigation and yield (typical of current approaches); and (ii) the stochastic response of yield and total seasonal irrigation to the choice of an intraseasonal soil moisture target and irrigated area. Irrigated area (the extensive margin decision) and per-area irrigation intensity (the intensive margin decision) are then calculated for different seasonal water restrictions (corresponding to regulatory policies) and well yield constraints on intraseasonal abstraction rates (corresponding to aquifer system limits). Profit- and utility-maximising decisions are determined assuming risk neutrality and varying degrees of risk aversion, respectively. Our results demonstrate that the formulation of the production function has a significant impact on the response to water scarcity. For low well yields, which are the major concern

  7. Collective Decision Dynamics in Group Evacuation: Modeling Tradeoffs and Optimal Behavior

    CERN Document Server

    Schlesinger, Kimberly J; Ali, Imtiaz; Carlson, Jean M

    2016-01-01

    Quantifying uncertainties in collective human behavior and decision making is crucial for ensuring public health and safety, enabling effective disaster response, informing the design of transportation and communication networks, and guiding the development of new technologies. However, modeling and predicting such behavior is notoriously difficult, due to the influence of a variety of complex factors such as the availability and uncertainty of information, the interaction and influence of social groups and networks, the degree of risk or time pressure involved in a situation, and differences in individual personalities and preferences. Here, we develop a stochastic model of human decision making to describe the empirical behavior of subjects in a controlled experiment simulating a natural disaster scenario. We compare the observed behavior to that of statistically optimal Bayesian decision makers, quantifying the extent to which human decisions are optimal and identifying the conditions in which sub-optimal ...

  8. Decision Making Models Using Weather Forecast Information

    OpenAIRE

    Hiramatsu, Akio; Huynh, Van-Nam; Nakamori, Yoshiteru

    2007-01-01

    The quality of weather forecast has gradually improved, but weather information such as precipitation forecast is still uncertainty. Meteorologists have studied the use and economic value of weather information, and users have to translate weather information into their most desirable action. To maximize the economic value of users, the decision maker should select the optimum course of action for his company or project, based on an appropriate decision strategy under uncertain situations. In...

  9. A decision-making model for engineering designers

    DEFF Research Database (Denmark)

    Ahmed, S.; Hansen, Claus Thorp

    2002-01-01

    This paper describes research that combines the generic decision-making model of Hansen, together with design strategies employed by experienced engineering designers. The relationship between the six decision-making sub-activities and the eight design strategies are examined. By combining these ...... these two understandings of the design process, a model has been developed, which describes the different types of decision made during the design process together with strategies that aid the designer in making decisions.......This paper describes research that combines the generic decision-making model of Hansen, together with design strategies employed by experienced engineering designers. The relationship between the six decision-making sub-activities and the eight design strategies are examined. By combining...

  10. Relevance of a Managerial Decision-Model to Educational Administration.

    Science.gov (United States)

    Lundin, Edward.; Welty, Gordon

    The rational model of classical economic theory assumes that the decision maker has complete information on alternatives and consequences, and that he chooses the alternative that maximizes expected utility. This model does not allow for constraints placed on the decision maker resulting from lack of information, organizational pressures,…

  11. Optimal pricing decision model based on activity-based costing

    Institute of Scientific and Technical Information of China (English)

    王福胜; 常庆芳

    2003-01-01

    In order to find out the applicability of the optimal pricing decision model based on conventional costbehavior model after activity-based costing has given strong shock to the conventional cost behavior model andits assumptions, detailed analyses have been made using the activity-based cost behavior and cost-volume-profitanalysis model, and it is concluded from these analyses that the theory behind the construction of optimal pri-cing decision model is still tenable under activity-based costing, but the conventional optimal pricing decisionmodel must be modified as appropriate to the activity-based costing based cost behavior model and cost-volume-profit analysis model, and an optimal pricing decision model is really a product pricing decision model construc-ted by following the economic principle of maximizing profit.

  12. Implications of the KONVERGENCE Model for Difficult Cleanup Decisions

    Energy Technology Data Exchange (ETDEWEB)

    Piet, Steven James; Dakins, Maxine Ellen; Gibson, Patrick Lavern; Joe, Jeffrey Clark; Kerr, Thomas A; Nitschke, Robert Leon

    2002-08-04

    Abstract—Some cleanup decisions, such as cleanup of intractable contaminated sites or disposal of spent nuclear fuel, have proven difficult to make. Such decisions face high resistance to agreement from stakeholders possibly because they do not trust the decision makers, view the consequences of being wrong as too high, etc. Our project’s goal is to improve sciencebased cleanup decision-making. This includes diagnosing intractable situations, as a step to identifying a path toward sustainable solutions. Companion papers describe the underlying philosophy of the KONVERGENCE Model for Sustainable Decisions,1 and the overall framework and process steps.2 Where knowledge, values, and resources converge (the K, V, and R in KONVERGENCE), you will find a sustainable decision – a decision that works over time. For intractable cases, serious consideration of the adaptable class of alternatives is warranted – if properly implemented and packaged.

  13. Issues in Developing a Normative Descriptive Model for Dyadic Decision Making

    Science.gov (United States)

    Serfaty, D.; Kleinman, D. L.

    1984-01-01

    Most research in modelling human information processing and decision making has been devoted to the case of the single human operator. In the present effort, concepts from the fields of organizational behavior, engineering psychology, team theory and mathematical modelling are merged in an attempt to consider first the case of two cooperating decisionmakers (the Dyad) in a multi-task environment. Rooted in the well-known Dynamic Decision Model (DDM), the normative descriptive approach brings basic cognitive and psychophysical characteristics inherent to human behavior into a team theoretic analytic framework. An experimental paradigm, involving teams in dynamic decision making tasks, is designed to produce the data with which to build the theoretical model.

  14. Breakthrough in the Human Decision Making Based on an Unconscious Origin of Free Will

    OpenAIRE

    Dubois, Daniel

    2010-01-01

    This paper deals with a breakthrough in the concept of free will in the human decision making. It is assumed that the consciousness and unconsciousness show the same mind processes in the human brain. The decision making initiates unconsciously in the human brain, and, eventually, becomes a conscious decision. So the free will is unconsciously prepared in the human brain. Then I conjecture that what is called the conscious human brain is just the enlightening of some parts of the unconscious ...

  15. Hierarchical decision modeling essays in honor of Dundar F. Kocaoglu

    CERN Document Server

    2016-01-01

    This volume, developed in honor of Dr. Dundar F. Kocaoglu, aims to demonstrate the applications of the Hierarchical Decision Model (HDM) in different sectors and its capacity in decision analysis. It is comprised of essays from noted scholars, academics and researchers of engineering and technology management around the world. This book is organized into four parts: Technology Assessment, Strategic Planning, National Technology Planning and Decision Making Tools. Dr. Dundar F. Kocaoglu is one of the pioneers of multiple decision models using hierarchies, and creator of the HDM in decision analysis. HDM is a mission-oriented method for evaluation and/or selection among alternatives. A wide range of alternatives can be considered, including but not limited to, different technologies, projects, markets, jobs, products, cities to live in, houses to buy, apartments to rent, and schools to attend. Dr. Kocaoglu’s approach has been adopted for decision problems in many industrial sectors, including electronics rese...

  16. IDENTIFYING OPERATIONAL REQUIREMENTS TO SELECT SUITABLE DECISION MODELS FOR A PUBLIC SECTOR EPROCUREMENT DECISION SUPPORT SYSTEM

    Directory of Open Access Journals (Sweden)

    Mohamed Adil

    2014-10-01

    Full Text Available Public sector procurement should be a transparent and fair process. Strict legal requirements are enforced on public sector procurement to make it a standardised process. To make fair decisions on selecting suppliers, a practical method which adheres to legal requirements is important. The research that is the base for this paper aimed at identifying a suitable Multi-Criteria Decision Analysis (MCDA method for the specific legal and functional needs of the Maldivian Public Sector. To identify such operational requirements, a set of focus group interviews were conducted in the Maldives with public officials responsible for procurement decision making. Based on the operational requirements identified through focus groups, criteria-based evaluation is done on published MCDA methods to identify the suitable methods for e-procurement decision making. This paper describes the identification of the operational requirements and the results of the evaluation to select suitable decision models for the Maldivian context.

  17. Electronic market models for decision support systems on the Web

    Institute of Scientific and Technical Information of China (English)

    谢勇; 王红卫; 费奇

    2004-01-01

    With the prevalence of the Web, most decision-makers are likely to use the Web to support their decision-making. Web-based technologies are leading a major stream of researching decision support systems (DSS). We propose a formal definition and a conceptual framework for Web-based open DSS (WODSS). The formal definition gives an overall view of WODSS, and the conceptual framework based on browser/broker/server computing mode employs the electronic market to mediate decision-makers and providers, and facilitate sharing and reusing of decision resources. We also develop an admitting model, a trading model and a competing model of electronic market in WODSS based on market theory in economics. These models reveal the key mechanisms that drive WODSS operate efficiently.

  18. The importance of imagination (or lack thereof) in artificial, human and quantum decision making.

    Science.gov (United States)

    Gustafson, Karl

    2016-01-13

    Enlarging upon experiments and analysis that I did jointly some years ago, in which artificial (symbolic, neural-net and pattern) learning and generalization were compared with that of humans, I will emphasize the role of imagination (or lack thereof) in artificial, human and quantum cognition and decision-making processes. Then I will look in more detail at some of the 'engineering details' of its implementation (or lack thereof) in each of these settings. In other words, the question posed is: What is actually happening? For example, we previously found that humans overwhelmingly seek, create or imagine context in order to provide meaning when presented with abstract, apparently incomplete, contradictory or otherwise untenable decision-making situations. Humans are intolerant of contradiction and will greatly simplify to avoid it. They can partially correlate but do not average. Human learning is not Boolean. These and other human reasoning properties will then be taken to critique how well artificial intelligence methods and quantum mechanical modelling might compete with them in decision-making tasks within psychology and economics.

  19. TWO-STAGE DECISION MODEL OF SOY FOOD CONSUMPTION BEHAVIOR

    OpenAIRE

    Rimal, Arbindra; Balasubramanian, Siva K.; Moon, Wanki

    2004-01-01

    Our study examined the role of soy health benefits in consumers' soy consumption decision. Given the large number of respondents who reported no consumption of soy products per month, it was important to model the decision of whether or not to participate in soy market separately from the consumption intensity decision. Estimation results demonstrate that knowledge of health benefits affects both the likelihood of participation and consumption intensity. That is, consumers with higher soy hea...

  20. The roles of dopamine and serotonin in decision making: evidence from pharmacological experiments in humans.

    Science.gov (United States)

    Rogers, Robert D

    2011-01-01

    Neurophysiological experiments in primates, alongside neuropsychological and functional magnetic resonance investigations in humans, have significantly enhanced our understanding of the neural architecture of decision making. In this review, I consider the more limited database of experiments that have investigated how dopamine and serotonin activity influences the choices of human adults. These include those experiments that have involved the administration of drugs to healthy controls, experiments that have tested genotypic influences upon dopamine and serotonin function, and, finally, some of those experiments that have examined the effects of drugs on the decision making of clinical samples. Pharmacological experiments in humans are few in number and face considerable methodological challenges in terms of drug specificity, uncertainties about pre- vs post-synaptic modes of action, and interactions with baseline cognitive performance. However, the available data are broadly consistent with current computational models of dopamine function in decision making and highlight the dissociable roles of dopamine receptor systems in the learning about outcomes that underpins value-based decision making. Moreover, genotypic influences on (interacting) prefrontal and striatal dopamine activity are associated with changes in choice behavior that might be relevant to understanding exploratory behaviors and vulnerability to addictive disorders. Manipulations of serotonin in laboratory tests of decision making in human participants have provided less consistent results, but the information gathered to date indicates a role for serotonin in learning about bad decision outcomes, non-normative aspects of risk-seeking behavior, and social choices involving affiliation and notions of fairness. Finally, I suggest that the role played by serotonin in the regulation of cognitive biases, and representation of context in learning, point toward a role in the cortically mediated cognitive

  1. Bayesian decision making in human collectives with binary choices

    CERN Document Server

    Eguíluz, Víctor M; Fernández-Gracia, J

    2015-01-01

    Here we focus on the description of the mechanisms behind the process of information aggregation and decision making, a basic step to understand emergent phenomena in society, such as trends, information spreading or the wisdom of crowds. In many situations, agents choose between discrete options. We analyze experimental data on binary opinion choices in humans. The data consists of two separate experiments in which humans answer questions with a binary response, where one is correct and the other is incorrect. The questions are answered without and with information on the answers of some previous participants. We find that a Bayesian approach captures the probability of choosing one of the answers. The influence of peers is uncorrelated with the difficulty of the question. The data is inconsistent with Weber's law, which states that the probability of choosing an option depends on the proportion of previous answers choosing that option and not on the total number of those answers. Last, the present Bayesian ...

  2. Decision support modeling for milk valorization

    NARCIS (Netherlands)

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating Frie

  3. Modeling uncertainty in requirements engineering decision support

    Science.gov (United States)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  4. Modeling uncertainty in requirements engineering decision support

    Science.gov (United States)

    Feather, Martin S.; Maynard-Zhang, Pedrito; Kiper, James D.

    2005-01-01

    One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

  5. Decision support modeling for milk valorization

    NARCIS (Netherlands)

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating

  6. Decision support modeling for milk valorization

    NARCIS (Netherlands)

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating Frie

  7. How and Why Decision Models Influence Marketing Resource Allocations

    NARCIS (Netherlands)

    G.L. Lilien (Gary); A. Rangaswamy (Arvind); K. Starke (Katrin); G.H. van Bruggen (Gerrit)

    2001-01-01

    textabstractWe study how and why model-based Decision Support Systems (DSSs) influence managerial decision making, in the context of marketing budgeting and resource allocation. We consider several questions: (1) What does it mean for a DSS to be "good?"; (2) What is the relationship between an anch

  8. A decision-making model for engineering designers

    DEFF Research Database (Denmark)

    Ahmed, S.; Hansen, Claus Thorp

    2002-01-01

    This paper describes research that combines the generic decision-making model of Hansen, together with design strategies employed by experienced engineering designers. The relationship between the six decision-making sub-activities and the eight design strategies are examined. By combining...

  9. A Signal Detection Model of Compound Decision Tasks

    Science.gov (United States)

    2006-12-01

    strict isolation (for many examples of such models see Egan, 1975; Macmillan & Creelman , 1991). The result has been twofold: A rich corpus of decision...Macmillan & Creelman , 1991). It is important to point out that SDT models are primarily decision models. They specify the rules and procedures for how...Broadbent, 1958; Macmillan & Creelman , 1991; Nolte & Jaarsma, 1967; Swensson & Judy, 1981; Tanner & Norman, 1954). To better understand how these two

  10. The role of business intelligence in decision process modeling

    Directory of Open Access Journals (Sweden)

    Višnja Istrat

    2015-10-01

    Full Text Available Decision making is a very significant and complex function of management that requires methods and techniques that simplify the process of choosing the best alternative. In modern business, the challenge for managers is to find the alternatives for improving the decision-making process. Decisions directly affect profit generation and positioning of the company in the market. It is well-known that people dealt with the phenomenon of decision making in each phase of the development of society, which has triggered the need to learn more about this process. The main contribution of this paper is to show the significance of business intelligence tools and techniques as support to the decision making process of managers. Research results have shown that business intelligence plays an enormous role in modern decision process modeling.

  11. Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges.

    Science.gov (United States)

    Klabunde, Anna; Willekens, Frans

    We review agent-based models (ABM) of human migration with respect to their decision-making rules. The most prominent behavioural theories used as decision rules are the random utility theory, as implemented in the discrete choice model, and the theory of planned behaviour. We identify the critical choices that must be made in developing an ABM, namely the modelling of decision processes and social networks. We also discuss two challenges that hamper the widespread use of ABM in the study of migration and, more broadly, demography and the social sciences: (a) the choice and the operationalisation of a behavioural theory (decision-making and social interaction) and (b) the selection of empirical evidence to validate the model. We offer advice on how these challenges might be overcome.

  12. Perspective and circumstance in making decisions:The 4D model of the world of enterprise

    OpenAIRE

    Acevedo Borrego, Adolfo Oswaldo; UNMSM

    2014-01-01

    To understand and solve business problems, the decision maker has a basic orientation to any dimensión of the organization. The 4 dimensións model is based on the perspective to understand and manipulate the business world: technical perspective that manages things and human perspective that is responsible for directing people to the task and performance, integration of both perspectives defines the basic preference of decision maker. The circumstance, that represents the problematic situatio...

  13. A spiral model of musical decision-making

    Directory of Open Access Journals (Sweden)

    Daniel eBangert

    2014-04-01

    Full Text Available This paper describes a model of how musicians make decisions about performing notated music. The model builds on psychological theories of decision-making and was developed from empirical studies of Western art music performance that aimed to identify intuitive and deliberate processes of decision-making, a distinction consistent with dual-process theories of cognition. The model proposes that the proportion of intuitive (Type 1 and deliberate (Type 2 decision-making processes changes with increasing expertise and conceptualises this change as movement along a continually narrowing upward spiral where the primary axis signifies principal decision-making type and the vertical axis marks level of expertise. The model is intended to have implications for the development of expertise as described in two main phases. The first is movement from a primarily intuitive approach in the early stages of learning towards greater deliberation as analytical techniques are applied during practice. The second phase occurs as deliberate decisions gradually become automatic (procedural, increasing the role of intuitive processes. As a performer examines more issues or reconsiders decisions, the spiral motion towards the deliberate side and back to the intuitive is repeated indefinitely. With increasing expertise, the spiral tightens to signify greater control over decision type selection. The model draws on existing theories, particularly Evans’ (2011 Intervention Model of dual-process theories, Cognitive Continuum Theory (Hammond et al., 1987; Hammond, 2007, and Baylor’s (2001 U-shaped model for the development of intuition by level of expertise. By theorising how musical decision-making operates over time and with increasing expertise, this model could be used as a framework for future research in music performance studies and performance science more generally.

  14. Validation of decision-making models and analysis of decision variables in the rat basal ganglia.

    Science.gov (United States)

    Ito, Makoto; Doya, Kenji

    2009-08-05

    Reinforcement learning theory plays a key role in understanding the behavioral and neural mechanisms of choice behavior in animals and humans. Especially, intermediate variables of learning models estimated from behavioral data, such as the expectation of reward for each candidate choice (action value), have been used in searches for the neural correlates of computational elements in learning and decision making. The aims of the present study are as follows: (1) to test which computational model best captures the choice learning process in animals and (2) to elucidate how action values are represented in different parts of the corticobasal ganglia circuit. We compared different behavioral learning algorithms to predict the choice sequences generated by rats during a free-choice task and analyzed associated neural activity in the nucleus accumbens (NAc) and ventral pallidum (VP). The major findings of this study were as follows: (1) modified versions of an action-value learning model captured a variety of choice strategies of rats, including win-stay-lose-switch and persevering behavior, and predicted rats' choice sequences better than the best multistep Markov model; and (2) information about action values and future actions was coded in both the NAc and VP, but was less dominant than information about trial types, selected actions, and reward outcome. The results of our model-based analysis suggest that the primary role of the NAc and VP is to monitor information important for updating choice behaviors. Information represented in the NAc and VP might contribute to a choice mechanism that is situated elsewhere.

  15. Decision support modeling for milk valorization

    OpenAIRE

    Banaszewska, A.

    2014-01-01

    The research presented in this thesis concerns decision problems in practice that require structured, precise, scientific studies to provide strong, reliable answers. An opportunity to contribute to both practice and science emerged in 2008 when two large, Dutch dairy companies merged, creating FrieslandCampina (FC), which was the fourth largest dairy company in the world at that time. In 2009, a new Milk Valorization & Allocation (MVA) department was created at the corporate level to opt...

  16. Multi-species Management Using Modeling and Decision Theory Applications to Integrated Natural Resources Management Planning

    Science.gov (United States)

    2008-06-01

    of the decision maker, risk and uncertainty. Application of decision tools clarifies the logic and facts that support decisions. Resnik (1987...Structured decision making explicitly facilitates selection among alternatives based on their consequences ( Resnik 1987). Decision theory incorporates...species populations. Human and Ecological Risk Assessment, 9(4):889-906 Resnik , M.D. (1987). Choices: An Introduction to Decision Theory. University of

  17. Multi-person Decision Model for Unfinished Construction Project

    Directory of Open Access Journals (Sweden)

    Christiono Utomo

    2010-05-01

    Full Text Available This paper discusses a proposed model of multi-person decision on prioritizing selection with regard to continuing or terminating unfinished construction projects. This involved multiple steps including determining criteria and sub criteria, selecting and weighting of alternatives, optimizing, and analyzing coalition formation and agreement option. Criteria and sub criteria that were obtained from perspectives of 120 project managers are the first basis to construct decision hierarchy. The model is implemented in one of the biggest private construction projects in Indonesia. The implementation was based on the Analytic Hierarchy Process for multi criteria decision involving coalition and agreement options in a multi-person decision. Goal Programming was used to optimize based on cost constrains. The results demonstrate a process of multiperson decision to select priorities of each alternative to each decision and concluded that some of the projects were continued, postponed or terminated. The new direction of research presented in this paper presents some interesting challenges to those involved in modeling computer-based multi-person decision support utilizing both Multi Agent System and Multi Criteria Decision Making.

  18. Computational human body models

    NARCIS (Netherlands)

    Wismans, J.S.H.M.; Happee, R.; Dommelen, J.A.W. van

    2005-01-01

    Computational human body models are widely used for automotive crashsafety research and design and as such have significantly contributed to a reduction of traffic injuries and fatalities. Currently crash simulations are mainly performed using models based on crash-dummies. However crash dummies dif

  19. Computational human body models

    NARCIS (Netherlands)

    Wismans, J.S.H.M.; Happee, R.; Dommelen, J.A.W. van

    2005-01-01

    Computational human body models are widely used for automotive crashsafety research and design and as such have significantly contributed to a reduction of traffic injuries and fatalities. Currently crash simulations are mainly performed using models based on crash-dummies. However crash dummies

  20. Leveraging human decision making through the optimal management of centralized resources

    Science.gov (United States)

    Hyden, Paul; McGrath, Richard G.

    2016-05-01

    Combining results from mixed integer optimization, stochastic modeling and queuing theory, we will advance the interdisciplinary problem of efficiently and effectively allocating centrally managed resources. Academia currently fails to address this, as the esoteric demands of each of these large research areas limits work across traditional boundaries. The commercial space does not currently address these challenges due to the absence of a profit metric. By constructing algorithms that explicitly use inputs across boundaries, we are able to incorporate the advantages of using human decision makers. Key improvements in the underlying algorithms are made possible by aligning decision maker goals with the feedback loops introduced between the core optimization step and the modeling of the overall stochastic process of supply and demand. A key observation is that human decision-makers must be explicitly included in the analysis for these approaches to be ultimately successful. Transformative access gives warfighters and mission owners greater understanding of global needs and allows for relationships to guide optimal resource allocation decisions. Mastery of demand processes and optimization bottlenecks reveals long term maximum marginal utility gaps in capabilities.

  1. A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

    Science.gov (United States)

    Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

    2015-01-01

    In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

  2. The ethical decision making model in obstetrics and gynaecology practice

    Directory of Open Access Journals (Sweden)

    Nazimah Idris

    2014-01-01

    Full Text Available This paper attempts to utilise clinical scenarios where ethical issues are embedded and requires appropriate application of the steps of the framework mentioned. A step by step sequential approach is adopted to illustrate how the ‘ethical decision model ‘can be used to resolve ethical problems to arrive at a reasonable conclusion. The UNESCO ethical method of reasoning is used as the framework for decision making. Physicianeducators should be competent to use ethical decision models as well as best available scientific evidence to be able to arrive at the best decision for patient care as well as teach health professional trainees how reasonable treatment decisions can be made within the perimeter of medical law and social justice.

  3. Designing Human-Centered Systems for Reflective Decision Making

    NARCIS (Netherlands)

    Pommeranz, A.

    2012-01-01

    Taking major life decisions, e.g. what career to follow, is difficult and sometimes emotional. One has to find out what exactly one wants, consider the long-term consequences of the decisions and be empathetic for loved ones affected by the decisions. Decision making also deals with establishing and

  4. Designing Human-Centered Systems for Reflective Decision Making

    NARCIS (Netherlands)

    Pommeranz, A.

    2012-01-01

    Taking major life decisions, e.g. what career to follow, is difficult and sometimes emotional. One has to find out what exactly one wants, consider the long-term consequences of the decisions and be empathetic for loved ones affected by the decisions. Decision making also deals with establishing and

  5. An analysis of symbolic linguistic computing models in decision making

    Science.gov (United States)

    Rodríguez, Rosa M.; Martínez, Luis

    2013-01-01

    It is common that experts involved in complex real-world decision problems use natural language for expressing their knowledge in uncertain frameworks. The language is inherent vague, hence probabilistic decision models are not very suitable in such cases. Therefore, other tools such as fuzzy logic and fuzzy linguistic approaches have been successfully used to model and manage such vagueness. The use of linguistic information implies to operate with such a type of information, i.e. processes of computing with words (CWW). Different schemes have been proposed to deal with those processes, and diverse symbolic linguistic computing models have been introduced to accomplish the linguistic computations. In this paper, we overview the relationship between decision making and CWW, and focus on symbolic linguistic computing models that have been widely used in linguistic decision making to analyse if all of them can be considered inside of the CWW paradigm.

  6. Optimization for decision making linear and quadratic models

    CERN Document Server

    Murty, Katta G

    2010-01-01

    While maintaining the rigorous linear programming instruction required, Murty's new book is unique in its focus on developing modeling skills to support valid decision-making for complex real world problems, and includes solutions to brand new algorithms.

  7. Multi-level decision making models, methods and applications

    CERN Document Server

    Zhang, Guangquan; Gao, Ya

    2015-01-01

    This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

  8. MoCog1: A computer simulation of recognition-primed human decision making, considering emotions

    Science.gov (United States)

    Gevarter, William B.

    1992-01-01

    The successful results of the first stage of a research effort to develop a versatile computer model of motivated human cognitive behavior are reported. Most human decision making appears to be an experience-based, relatively straightforward, largely automatic response to situations, utilizing cues and opportunities perceived from the current environment. The development, considering emotions, of the architecture and computer program associated with such 'recognition-primed' decision-making is described. The resultant computer program (MoCog1) was successfully utilized as a vehicle to simulate earlier findings that relate how an individual's implicit theories orient the individual toward particular goals, with resultant cognitions, affects, and behavior in response to their environment.

  9. Reduced model-based decision-making in schizophrenia.

    Science.gov (United States)

    Culbreth, Adam J; Westbrook, Andrew; Daw, Nathaniel D; Botvinick, Matthew; Barch, Deanna M

    2016-08-01

    Individuals with schizophrenia have a diminished ability to use reward history to adaptively guide behavior. However, tasks traditionally used to assess such deficits often rely on multiple cognitive and neural processes, leaving etiology unresolved. In the current study, we adopted recent computational formalisms of reinforcement learning to distinguish between model-based and model-free decision-making in hopes of specifying mechanisms associated with reinforcement-learning dysfunction in schizophrenia. Under this framework, decision-making is model-free to the extent that it relies solely on prior reward history, and model-based if it relies on prospective information such as motivational state, future consequences, and the likelihood of obtaining various outcomes. Model-based and model-free decision-making was assessed in 33 schizophrenia patients and 30 controls using a 2-stage 2-alternative forced choice task previously demonstrated to discern individual differences in reliance on the 2 forms of reinforcement-learning. We show that, compared with controls, schizophrenia patients demonstrate decreased reliance on model-based decision-making. Further, parameter estimates of model-based behavior correlate positively with IQ and working memory measures, suggesting that model-based deficits seen in schizophrenia may be partially explained by higher-order cognitive deficits. These findings demonstrate specific reinforcement-learning and decision-making deficits and thereby provide valuable insights for understanding disordered behavior in schizophrenia. (PsycINFO Database Record

  10. Human migraine models

    DEFF Research Database (Denmark)

    Iversen, Helle Klingenberg

    2001-01-01

    The need for experimental models is obvious. In animal models it is possible to study vascular responses, neurogenic inflammation, c-fos expression etc. However, the pathophysiology of migraine remains unsolved, why results from animal studies not directly can be related to the migraine attack......, which is a human experience. A set-up for investigations of experimental headache and migraine in humans, has been evaluated and headache mechanisms explored by using nitroglycerin and other headache-inducing agents. Nitric oxide (NO) or other parts of the NO activated cascade seems to be responsible...

  11. Designing of a Personality Based Emotional Decision Model for Generating Various Emotional Behavior of Social Robots

    Directory of Open Access Journals (Sweden)

    Ho Seok Ahn

    2014-01-01

    Full Text Available All humans feel emotions, but individuals express their emotions differently because each has a different personality. We design an emotional decision model that focuses on the personality of individuals. The personality-based emotional decision model is designed with four linear dynamics, viz. reactive dynamic system, internal dynamic system, emotional dynamic system, and behavior dynamic system. Each dynamic system calculates the output values that reflect the personality, by being used as system matrices, input matrices, and output matrices. These responses are reflected in the final emotional behavior through a behavior dynamic system as with humans. The final emotional behavior includes multiple emotional values, and a social robot shows various emotional expressions. We perform some experiments using the cyber robot system, to verify the efficiency of the personality-based emotional decision model that generates various emotions according to the personality.

  12. A neural model of decision making

    DEFF Research Database (Denmark)

    Larsen, Torben

    2008-01-01

    and inhibitory processes and EEG is still useful for research as a broader and direct measure of brain activity. On this background a new interdisciplinary field linking behavioural economics and neuroscience into a neuroeconomic discipline emerges. Recent reviews of neuroeconomics represent a platform...... for further development of neuroeconomics [McLean 1992 and Luria 1973].    An overview of neuroeconomics from an economic perspective reviewing 13 studies [Kenning and Plassman, 2005]. It is concluded that the first studies are explorative research focusing concepts crucial to modern economic theory...... such as fairness, trust, altruism, memory, learning and knowledge. The goal of neuroeconomics is stated as to provide a descriptive decision-making theory, which is not restricted to economic theory and more realistic than that of economic man.    Reviewing how neuroscience can inform economics [Camerer et al...

  13. Incorporating risk attitude into Markov-process decision models: importance for individual decision making.

    Science.gov (United States)

    Cher, D J; Miyamoto, J; Lenert, L A

    1997-01-01

    Most decision models published in the medical literature take a risk-neutral perspective. Under risk neutrality, the utility of a gamble is equivalent to its expected value and the marginal utility of living a given unit of time is the same regardless of when it occurs. Most patients, however, are not risk-neutral. Not only does risk aversion affect decision analyses when tradeoffs between short- and long-term survival are involved, it also affects the interpretation of time-tradeoff measures of health-state utility. The proportional time tradeoff under- or overestimates the disutility of an inferior health state, depending on whether the patient is risk-seeking or risk-averse (it is unbiased if the patient is risk-neutral). The authors review how risk attitude with respect to gambles for survival duration can be incorporated into decision models using the framework of risk-adjusted quality-adjusted life years (RA-QALYs). They present a simple extension of this framework that allows RA-QALYs to be calculated for Markov-process decision models. Using a previously published Markov-process model of surgical vs expectant treatment for benign prostatic hypertrophy (BPH), they show how attitude towards risk affects the expected number of QALYs calculated by the model. In this model, under risk neutrality, surgery was the preferred option. Under mild risk aversion, expectant treatment was the preferred option. Risk attitude is an important aspect of preferences that should be incorporated into decision models where one treatment option has upfront risks of morbidity or mortality.

  14. Building models for marketing decisions : past, present and future

    NARCIS (Netherlands)

    Leeflang, P.S.H.; Wittink, Dick R.

    2000-01-01

    We review five eras of model building in marketing, with special emphasis on the fourth and the fifth eras, the present and the future. At many firms managers now routinely use model-based results for marketing decisions. Given an increasing number of successful applications, the demand for models t

  15. Building models for marketing decisions : Past, present and future

    NARCIS (Netherlands)

    Leeflang, PSH; Wittink, DR

    2000-01-01

    We review five eras of model building in marketing, with special emphasis on the fourth and the fifth eras, the present and the future. At many firms managers now routinely use model-based results for marketing decisions. Given an increasing number of successful applications, the demand for models t

  16. A Decision Model for Locating Controversial Facilities

    Science.gov (United States)

    Mumphrey, Anthony J.; And Others

    1971-01-01

    Locating controversial public facilities, such as highways or airports, that generate significant public opposition requires a more sophisticated methodology than the traditional least cost" procedures for minimizing physical costs. Two models--a short-run political placation" model and a long-run welfare distribution" model--evaluate the…

  17. Learning Markov Decision Processes for Model Checking

    DEFF Research Database (Denmark)

    Mao, Hua; Chen, Yingke; Jaeger, Manfred

    2012-01-01

    Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm on...

  18. MULTI SUPPORT VECTOR MACHINES DECISION MODEL AND ITS APPLICATION

    Institute of Scientific and Technical Information of China (English)

    阎威武; 陈治纲; 邵惠鹤

    2002-01-01

    Support Vector Machines (SVM) is a powerful machine learning method developed from statistical learning theory and is currently an active field in artificial intelligent technology. SVM is sensitive to noise vectors near hyperplane since it is determined only by few support vectors. In this paper, Multi SVM decision model(MSDM)was proposed. MSDM consists of multiple SVMs and makes decision by synthetic information based on multi SVMs. MSDM is applied to heart disease diagnoses based on UCI benchmark data set. MSDM somewhat inproves the robust of decision system.

  19. Decision making in the transtheoretical model of behavior change.

    Science.gov (United States)

    Prochaska, James O

    2008-01-01

    Decision making is an integral part of the transtheoretical model of behavior change. Stage of change represents a temporal dimension for behavior change and has been the key dimension for integrating principles and processes of change from across leading theories of psychotherapy and behavior change. The decision-making variables representing the pros and cons of changing have been found to have systematic relationships across the stages of change for 50 health-related behaviors. Implications of these patterns of relationships are discussed in the context of helping patients make more effective decisions to decrease health risk behaviors and increase health-enhancing behaviors.

  20. The DO ART Model: An Ethical Decision-Making Model Applicable to Art Therapy

    Science.gov (United States)

    Hauck, Jessica; Ling, Thomson

    2016-01-01

    Although art therapists have discussed the importance of taking a positive stance in terms of ethical decision making (Hinz, 2011), an ethical decision-making model applicable for the field of art therapy has yet to emerge. As the field of art therapy continues to grow, an accessible, theoretically grounded, and logical decision-making model is…

  1. The DO ART Model: An Ethical Decision-Making Model Applicable to Art Therapy

    Science.gov (United States)

    Hauck, Jessica; Ling, Thomson

    2016-01-01

    Although art therapists have discussed the importance of taking a positive stance in terms of ethical decision making (Hinz, 2011), an ethical decision-making model applicable for the field of art therapy has yet to emerge. As the field of art therapy continues to grow, an accessible, theoretically grounded, and logical decision-making model is…

  2. Unicriterion Model: A Qualitative Decision Making Method That Promotes Ethics

    Directory of Open Access Journals (Sweden)

    Fernando Guilherme Silvano Lobo Pimentel

    2011-06-01

    Full Text Available Management decision making methods frequently adopt quantitativemodels of several criteria that bypass the question of whysome criteria are considered more important than others, whichmakes more difficult the task of delivering a transparent viewof preference structure priorities that might promote ethics andlearning and serve as a basis for future decisions. To tackle thisparticular shortcoming of usual methods, an alternative qualitativemethodology of aggregating preferences based on the rankingof criteria is proposed. Such an approach delivers a simpleand transparent model for the solution of each preference conflictfaced during the management decision making process. Themethod proceeds by breaking the decision problem into ‘two criteria– two alternatives’ scenarios, and translating the problem ofchoice between alternatives to a problem of choice between criteriawhenever appropriate. The unicriterion model method is illustratedby its application in a car purchase and a house purchasedecision problem.

  3. Overview 2010 of ARL Program on Network Science for Human Decision Making.

    Science.gov (United States)

    West, Bruce J

    2011-01-01

    The Army Research Laboratory program on the Network Science of Human Decision Making brings together researchers from a variety of disciplines to work on a complex research problem that defies confinement within any single discipline. Consequently, new and rewarding solutions have been obtained for a problem of importance to society and the Army, that being, the human dimension of complex networks. This program investigates the basic research foundation of a science of networks supporting the linkage between the cognitive and social domains as they relate to human decision making. The research strategy extends recent methods of non-equilibrium statistical physics to non-stationary, renewal stochastic processes characteristic of the interactions among nodes in complex networks. The theoretical analyses of complex networks, although mathematically rigorous, often elude analytic solutions and require simulation and computation to analyze the underlying dynamic process. The information transfer between two complex networks is calculated using the principle of complexity management as well as direct numerical calculation of the decision making model developed within the project.

  4. OVERVIEW 2010 OF ARL PROGRAM ON NETWORK SCIENCE FOR HUMAN DECISION MAKING

    Directory of Open Access Journals (Sweden)

    Bruce J West

    2011-11-01

    Full Text Available The Army Research Laboratory program on the Network Science of Human Decision Making brings together researchers from a variety of disciplines to work on a complex research problem that defies confinement within any single discipline. Consequently, new and rewarding solutions have been obtained for a problem of importance to society and the Army, that being, the human dimension of complex networks. This program investigates the basic research foundation of a science of networks supporting the linkage between the cognitive and social domains as they relate to human decision making. The research strategy extends recent methods of non-equilibrium statistical physics to non-stationary, renewal stochastic processes characteristic of the interactions among nodes in complex networks. The theoretical analyses of complex networks, although mathematically rigorous, often elude analytic solutions and require simulation and computation to analyze the underlying dynamic process. The information transfer between two complex networks is calculated using the Principle of Complexity Management (PCM as well as direct numerical calculation of the decision making model (DMM developed within the project.

  5. Human Factors Model

    Science.gov (United States)

    1993-01-01

    Jack is an advanced human factors software package that provides a three dimensional model for predicting how a human will interact with a given system or environment. It can be used for a broad range of computer-aided design applications. Jack was developed by the computer Graphics Research Laboratory of the University of Pennsylvania with assistance from NASA's Johnson Space Center, Ames Research Center and the Army. It is the University's first commercial product. Jack is still used for academic purposes at the University of Pennsylvania. Commercial rights were given to Transom Technologies, Inc.

  6. Open Models of Decision Support Towards a Framework

    OpenAIRE

    Diasio, Stephen Ray

    2012-01-01

    Aquesta tesi presenta un marc per als models oberts de suport a les decisions en les organitzacions. El treball es vehicula a través d’un compendi d’articles on s’analitzen els fluxos d’entrada i de sortida de coneixement en les organitzacions, així como les tecnologies existents de suport a les decisions. Es presenten els factors subjacents que impulsen nous models per a formes obertes de suport a la decisió. La tesis presenta un estudi de les distintes tipologies de models de suport a les d...

  7. The Intelligent Decision Support System Model of SARS

    Institute of Scientific and Technical Information of China (English)

    ZhouXingyu; ZhangJiang; LiuYang; XieYanqing; ZhangRan; ZhaoYang; HeZhongxiong

    2004-01-01

    Based on the intelligent decision support system, a new method was presented to defense the catastrophic infectious disease such as SARS, Bird Flu, etc.. By using All Set theory, the decision support system (DSS) model can be built to analyze the noise information and forecast the trend of the catastrophe then to give the method or policy to defend the disease. The model system is composed of four subsystems: the noise analysis subsystem, forecast and simulation subsystem, diagnosis subsystem and second recovery subsystem. They are discussed briefly in this paper. This model can be used not only for SARS but also for other paroxysmal accidences.

  8. Decision Support Model for Introduction of Gamification Solution Using AHP

    Directory of Open Access Journals (Sweden)

    Sangkyun Kim

    2014-01-01

    Full Text Available Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

  9. Decision support model for introduction of gamification solution using AHP.

    Science.gov (United States)

    Kim, Sangkyun

    2014-01-01

    Gamification means the use of various elements of game design in nongame contexts including workplace collaboration, marketing, education, military, and medical services. Gamification is effective for both improving workplace productivity and motivating employees. However, introduction of gamification is not easy because the planning and implementation processes of gamification are very complicated and it needs interdisciplinary knowledge such as information systems, organization behavior, and human psychology. Providing a systematic decision making method for gamification process is the purpose of this paper. This paper suggests the decision criteria for selection of gamification platform to support a systematic decision making process for managements. The criteria are derived from previous works on gamification, introduction of information systems, and analytic hierarchy process. The weights of decision criteria are calculated through a survey by the professionals on game, information systems, and business administration. The analytic hierarchy process is used to derive the weights. The decision criteria and weights provided in this paper could support the managements to make a systematic decision for selection of gamification platform.

  10. Entity Modeling and Immersive Decision Environments

    Science.gov (United States)

    2011-09-01

    enhanced visual displays. The team also demonstrated 6-degrees of freedom (6DoF) aero models in a real-time or near real-time training network, and...developed rule sets for functional handoff of aero models from one level of complexity to another to maximize computational capability. The above tasking...motion blur reduction shutter was used to systematically manipulate hold time causing luminance to co-vary with hold time. Thus, a fourth independent

  11. Towards autonomous decision-making: A probabilistic model for learning multi-user preferences

    NARCIS (Netherlands)

    M. Peters (Markus); W. Ketter (Wolfgang)

    2013-01-01

    textabstractInformation systems have revolutionized the provisioning of decision-relevant information, and decision support tools have improved human decisions in many domains. Autonomous decision- making, on the other hand, remains hampered by systems’ inability to faithfully capture human preferen

  12. DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Marília Gonçalves Dutra da Silva

    2016-04-01

    Full Text Available ABSTRACT This work aims to demonstrate the use of a mechanism to be applied in the development of the discrete-event simulation models that perform decision operations through the implementation of an artificial neural network. Actions that involve complex operations performed by a human agent in a process, for example, are often modeled in simplified form with the usual mechanisms of simulation software. Therefore, it was chosen a traffic system controlled by a traffic officer with a flow of vehicles and pedestrians to demonstrate the proposed solution. From a module built in simulation software itself, it was possible to connect the algorithm for intelligent decision to the simulation model. The results showed that the model elaborated responded as expected when it was submitted to actions, which required different decisions to maintain the operation of the system with changes in the flow of people and vehicles.

  13. Modeling Conflict And Exchange In Collective Decision Making

    NARCIS (Netherlands)

    Stokman, Frans N.

    1995-01-01

    Two dynamic models of collecuve decision maklng are Introduced and lllustrated wlth a simple example. A more extensive presentation and appllcauon concerning the European Community can be found In Bueno de Mesqulta and Stokman (19941. The two dynamlc models reflect two alternative views of collectiv

  14. Model based decision support for planning of road maintenance

    NARCIS (Netherlands)

    Worm, J.M.; Harten, van A.

    1996-01-01

    In this article we describe a Decision Support Model, based on Operational Research methods, for the multi-period planning of maintenance of bituminous pavements. This model is a tool for the road manager to assist in generating an optimal maintenance plan for a road. Optimal means: minimising the N

  15. A normative model of hospital marketing decision making.

    Science.gov (United States)

    Hammond, K L; Brown, G; Humphreys, N

    1993-01-01

    A hospital marketing model is proposed for use as a framework for applying marketing strategy and concepts to hospitals. The cells of the model, primarily summarizing the many decisions of the marketing management process as can be applied to hospitals, are justified by the health care marketing literature.

  16. Modeling Policy and Agricultural Decisions in Afghanistan

    CERN Document Server

    Widener, Michael J; Gros, Andreas; Metcalf, Sara; Bar-Yam, Yaneer

    2011-01-01

    Afghanistan is responsible for the majority of the world's supply of poppy crops, which are often used to produce illegal narcotics like heroin. This paper presents an agent-based model that simulates policy scenarios to characterize how the production of poppy can be dampened and replaced with licit crops over time. The model is initialized with spatial data, including transportation network and satellite-derived land use data. Parameters representing national subsidies, insurgent influence, and trafficking blockades are varied to represent different conditions that might encourage or discourage poppy agriculture. Our model shows that boundary-level interventions, such as targeted trafficking blockades at border locations, are critical in reducing the attractiveness of growing this illicit crop. The principle of least effort implies that interventions decrease to a minimal non-regressive point, leading to the prediction that increases in insurgency or other changes are likely to lead to worsening conditions,...

  17. Beyond pain: modeling decision-making deficits in chronic pain

    Science.gov (United States)

    Hess, Leonardo Emanuel; Haimovici, Ariel; Muñoz, Miguel Angel; Montoya, Pedro

    2014-01-01

    Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT) is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls (HCs). In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and HCs at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in HCs was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis. PMID:25136301

  18. Beyond pain: modeling decision-making deficits in chronic pain

    Directory of Open Access Journals (Sweden)

    Leonardo Emanuel Hess

    2014-08-01

    Full Text Available Risky decision-making seems to be markedly disrupted in patients with chronic pain, probably due to the high cost that impose pain and negative mood on executive control functions. Patients’ behavioral performance on decision-making tasks such as the Iowa Gambling Task (IGT is characterized by selecting cards more frequently from disadvantageous than from advantageous decks, and by switching often between competing responses in comparison with healthy controls. In the present study, we developed a simple heuristic model to simulate individuals’ choice behavior by varying the level of decision randomness and the importance given to gains and losses. The findings revealed that the model was able to differentiate the behavioral performance of patients with chronic pain and healthy controls at the group, as well as at the individual level. The best fit of the model in patients with chronic pain was yielded when decisions were not based on previous choices and when gains were considered more relevant than losses. By contrast, the best account of the available data in healthy controls was obtained when decisions were based on previous experiences and losses loomed larger than gains. In conclusion, our model seems to provide useful information to measure each individual participant extensively, and to deal with the data on a participant-by-participant basis.

  19. Multitask Efficiencies in the Decision Tree Model

    CERN Document Server

    Drucker, Andrew

    2008-01-01

    In Direct Sum problems [KRW], one tries to show that for a given computational model, the complexity of computing a collection $F = \\{f_i\\}$ of functions on independent inputs is approximately the sum of their individual complexities. In this paper, by contrast, we study the diversity of ways in which the joint computational complexity can behave when all the $f_i$ are evaluated on a \\textit{common} input. Fixing some model of computational cost, let $C_F(X): \\{0, 1\\}^l \\to \\mathbf{R}$ give the cost of computing the subcollection $\\{f_i(x): X_i = 1\\}$, on common input $x$. What constraints do the functions $C_F(X)$ obey, when $F$ is chosen freely? $C_F(X)$ will, for reasonable models, obey nonnegativity, monotonicity, and subadditivity. We show that, in the deterministic, adaptive query model, these are `essentially' the only constraints: for any function $C(X)$ obeying these properties and any $\\epsilon > 0$, there exists a family $F$ of boolean functions and a $T > 0$ such that for all $X \\in \\{0, 1\\}^l$, \\...

  20. Decision Support System for Resource Allocation Model

    Science.gov (United States)

    1989-04-01

    by Presutti and Trepp in their paper "Much Ado about EOQ." [2) The constraints used in the stock fund model are total stock fund dollars and limits on...Jersey, 1963. 2. Presutti, Victor J., Jr. and Trepp , Richard C., More Ado About Economic Order Ouantities (EOO), Operations Analysis Office

  1. Consumer's Online Shopping Influence Factors and Decision-Making Model

    Science.gov (United States)

    Yan, Xiangbin; Dai, Shiliang

    Previous research on online consumer behavior has mostly been confined to the perceived risk which is used to explain those barriers for purchasing online. However, perceived benefit is another important factor which influences consumers’ decision when shopping online. As a result, an integrated consumer online shopping decision-making model is developed which contains three elements—Consumer, Product, and Web Site. This model proposed relative factors which influence the consumers’ intention during the online shopping progress, and divided them into two different dimensions—mentally level and material level. We tested those factors with surveys, from both online volunteers and offline paper surveys with more than 200 samples. With the help of SEM, the experimental results show that the proposed model and method can be used to analyze consumer’s online shopping decision-making process effectively.

  2. Intelligent negotiation model for ubiquitous group decision scenarios

    Institute of Scientific and Technical Information of China (English)

    Joo CARNEIRO; Diogo MARTINHO; Goreti MARREIROS; Paulo NOVAIS

    2016-01-01

    Supporting group decision-making in ubiquitous contexts is a complex task that must deal with a large amount of factors to succeed. Here we propose an approach for an intelligent negotiation model to support the group decision-making process specifically designed for ubiquitous contexts. Our approach can be used by researchers that intend to include arguments, complex algorithms, and agents’ modeling in a negotiation model. It uses a social networking logic due to the type of communication employed by the agents and it intends to support the ubiquitous group decision-making process in a similar way to the real process, which simultaneously preserves the amount and quality of intelligence generated in face-to-face meetings. We propose a new look into this problem by considering and defining strategies to deal with important points such as the type of attributes in the multi- criterion problems, agents’ reasoning, and intelligent dialogues.

  3. Bridging groundwater models and decision support with a Bayesian network

    Science.gov (United States)

    Fienen, Michael N.; Masterson, John P.; Plant, Nathaniel G.; Gutierrez, Benjamin T.; Thieler, E. Robert

    2013-01-01

    Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

  4. Landslide risk models for decision making.

    Science.gov (United States)

    Bonachea, Jaime; Remondo, Juan; de Terán, José Ramón Díaz; González-Díez, Alberto; Cendrero, Antonio

    2009-11-01

    This contribution presents a quantitative procedure for landslide risk analysis and zoning considering hazard, exposure (or value of elements at risk), and vulnerability. The method provides the means to obtain landslide risk models (expressing expected damage due to landslides on material elements and economic activities in monetary terms, according to different scenarios and periods) useful to identify areas where mitigation efforts will be most cost effective. It allows identifying priority areas for the implementation of actions to reduce vulnerability (elements) or hazard (processes). The procedure proposed can also be used as a preventive tool, through its application to strategic environmental impact analysis (SEIA) of land-use plans. The underlying hypothesis is that reliable predictions about hazard and risk can be made using models based on a detailed analysis of past landslide occurrences in connection with conditioning factors and data on past damage. The results show that the approach proposed and the hypothesis formulated are essentially correct, providing estimates of the order of magnitude of expected losses for a given time period. Uncertainties, strengths, and shortcomings of the procedure and results obtained are discussed and potential lines of research to improve the models are indicated. Finally, comments and suggestions are provided to generalize this type of analysis.

  5. A Mining Algorithm for Extracting Decision Process Data Models

    Directory of Open Access Journals (Sweden)

    Cristina-Claudia DOLEAN

    2011-01-01

    Full Text Available The paper introduces an algorithm that mines logs of user interaction with simulation software. It outputs a model that explicitly shows the data perspective of the decision process, namely the Decision Data Model (DDM. In the first part of the paper we focus on how the DDM is extracted by our mining algorithm. We introduce it as pseudo-code and, then, provide explanations and examples of how it actually works. In the second part of the paper, we use a series of small case studies to prove the robustness of the mining algorithm and how it deals with the most common patterns we found in real logs.

  6. Weighted Hybrid Decision Tree Model for Random Forest Classifier

    Science.gov (United States)

    Kulkarni, Vrushali Y.; Sinha, Pradeep K.; Petare, Manisha C.

    2016-06-01

    Random Forest is an ensemble, supervised machine learning algorithm. An ensemble generates many classifiers and combines their results by majority voting. Random forest uses decision tree as base classifier. In decision tree induction, an attribute split/evaluation measure is used to decide the best split at each node of the decision tree. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation among them. The work presented in this paper is related to attribute split measures and is a two step process: first theoretical study of the five selected split measures is done and a comparison matrix is generated to understand pros and cons of each measure. These theoretical results are verified by performing empirical analysis. For empirical analysis, random forest is generated using each of the five selected split measures, chosen one at a time. i.e. random forest using information gain, random forest using gain ratio, etc. The next step is, based on this theoretical and empirical analysis, a new approach of hybrid decision tree model for random forest classifier is proposed. In this model, individual decision tree in Random Forest is generated using different split measures. This model is augmented by weighted voting based on the strength of individual tree. The new approach has shown notable increase in the accuracy of random forest.

  7. Value-directed human behavior analysis from video using partially observable Markov decision processes.

    Science.gov (United States)

    Hoey, Jesse; Little, James J

    2007-07-01

    This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the context in which they are acting, and a utility function. This learning makes explicit that the meaning of a behavior to an observer is contained in its relationship to actions and outcomes. An agent wishing to capitalize on these relationships must learn to distinguish the behaviors according to how they help the agent to maximize utility. The model we use is a partially observable Markov decision process, or POMDP. The video observations are integrated into the POMDP using a dynamic Bayesian network that creates spatial and temporal abstractions amenable to decision making at the high level. The parameters of the model are learned from training data using an a posteriori constrained optimization technique based on the expectation-maximization algorithm. The system automatically discovers classes of behaviors and determines which are important for choosing actions that optimize over the utility of possible outcomes. This type of learning obviates the need for labeled data from expert knowledge about which behaviors are significant and removes bias about what behaviors may be useful to recognize in a particular situation. We show results in three interactions: a single player imitation game, a gestural robotic control problem, and a card game played by two people.

  8. Decision Analysis Methods Used to Make Appropriate Investments in Human Exploration Capabilities and Technologies

    Science.gov (United States)

    Williams-Byrd, Julie; Arney, Dale C.; Hay, Jason; Reeves, John D.; Craig, Douglas

    2016-01-01

    , this paper will describe the processes that the NASA Langley Research Center (LaRC) Technology Assessment and Integration Team (TAIT) has used for several years and how those processes have been customized to meet customer needs while staying robust and defensible. This paper will show how HEOMD uses these analyses results to assist with making informed portfolio investment decisions. The paper will also highlight which human exploration capabilities and technologies typically rank high regardless of the specific design reference mission. The paper will conclude by describing future capability and technology ranking activities that will continue o leverage subject matter experts (SME) input while also incorporating more model-based analysis.

  9. The decision book fifty models for strategic thinking

    CERN Document Server

    Krogerus, Mikael

    2011-01-01

    Most of us face the same questions every day: What do I want? And how can I get it? How can I live more happily and work more efficiently? A worldwide bestseller, The Decision Book distils into a single volume the fifty best decision-making models used on MBA courses and elsewhere that will help you tackle these important questions - from the well known (the Eisenhower matrix for time management) to the less familiar but equally useful (the Swiss Cheese model). It will even show you how to remember everything you will have learned by the end of it. Stylish and compact, this little black book is a powerful asset. Whether you need to plot a presentation, assess someone's business idea or get to know yourself better, this unique guide will help you simplify any problem and take steps towards the right decision.

  10. Effect of time pressure and human judgment on decision making in three public sector organizations of Pakistan

    Directory of Open Access Journals (Sweden)

    Rizwan Saleem

    2011-02-01

    Full Text Available This study attempts to widen the effect of time pressure and human judgment on decision making. A census of three organizations named Project Management Organization (PMO, Accountant General Pakistan Revenues (AGPR and Controller General of Accountant (CGA was occupied. To demeanor this study a questionnaire tagged Decision Making, Time Pressure and Human Judgment was used for the assortment of data. The questionnaire was predominantly designed to accomplish the objectives of the study. The total number of observations was eighty two and the Arithmetic Mean Score of decision making, time pressure and human judgment were 2.532, 2.527 and 2.395 respectively. The significance level of the model was 0.000 which illustrates maximum significant level. As p-value is less than .05 so it can be assumed that the variables elected for the study are decidedly significant.

  11. Simple model for multiple-choice collective decision making.

    Science.gov (United States)

    Lee, Ching Hua; Lucas, Andrew

    2014-11-01

    We describe a simple model of heterogeneous, interacting agents making decisions between n≥2 discrete choices. For a special class of interactions, our model is the mean field description of random field Potts-like models and is effectively solved by finding the extrema of the average energy E per agent. In these cases, by studying the propagation of decision changes via avalanches, we argue that macroscopic dynamics is well captured by a gradient flow along E. We focus on the permutation symmetric case, where all n choices are (on average) the same, and spontaneous symmetry breaking (SSB) arises purely from cooperative social interactions. As examples, we show that bimodal heterogeneity naturally provides a mechanism for the spontaneous formation of hierarchies between decisions and that SSB is a preferred instability to discontinuous phase transitions between two symmetric points. Beyond the mean field limit, exponentially many stable equilibria emerge when we place this model on a graph of finite mean degree. We conclude with speculation on decision making with persistent collective oscillations. Throughout the paper, we emphasize analogies between methods of solution to our model and common intuition from diverse areas of physics, including statistical physics and electromagnetism.

  12. Modeling bursts and heavy tails in human dynamics

    OpenAIRE

    Vazquez, A.; Oliveira, J. Gama; Dezso, Z.; Goh, K. -I.; Kondor, I.; Barabasi, A. -L.

    2005-01-01

    Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. We provide direct evidence that for five human activity patterns the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision ba...

  13. Multi-criteria decision model for retrofitting existing buildings

    Directory of Open Access Journals (Sweden)

    M. D. Bostenaru Dan

    2004-01-01

    Full Text Available Decision is an element in the risk management process. In this paper the way how science can help in decision making and implementation for retrofitting buildings in earthquake prone urban areas is investigated. In such interventions actors from various spheres are involved. Their interests range among minimising the intervention for maximal preservation or increasing it for seismic safety. Research was conducted to see how to facilitate collaboration between these actors. A particular attention was given to the role of time in actors' preferences. For this reason, on decision level, both the processural and the personal dimension of risk management, the later seen as a task, were considered. A systematic approach was employed to determine the functional structure of a participative decision model. Three layers on which actors implied in this multi-criteria decision problem interact were identified: town, building and element. So-called 'retrofit elements' are characteristic bearers in the architectural survey, engineering simulations, costs estimation and define the realms perceived by the inhabitants. This way they represent an interaction basis for the interest groups considered in a deeper study. Such orientation means for actors' interaction were designed on other levels of intervention as well. Finally, an 'experiment' for the implementation of the decision model is presented: a strategic plan for an urban intervention towards reduction of earthquake hazard impact through retrofitting. A systematic approach proves thus to be a very good communication basis among the participants in the seismic risk management process. Nevertheless, it can only be applied in later phases (decision, implementation, control only, since it serves verifying and improving solution and not developing the concept. The 'retrofit elements' are a typical example of the detailing degree reached in the retrofit design plans in these phases.

  14. Emulation Modeling with Bayesian Networks for Efficient Decision Support

    Science.gov (United States)

    Fienen, M. N.; Masterson, J.; Plant, N. G.; Gutierrez, B. T.; Thieler, E. R.

    2012-12-01

    Bayesian decision networks (BDN) have long been used to provide decision support in systems that require explicit consideration of uncertainty; applications range from ecology to medical diagnostics and terrorism threat assessments. Until recently, however, few studies have applied BDNs to the study of groundwater systems. BDNs are particularly useful for representing real-world system variability by synthesizing a range of hydrogeologic situations within a single simulation. Because BDN output is cast in terms of probability—an output desired by decision makers—they explicitly incorporate the uncertainty of a system. BDNs can thus serve as a more efficient alternative to other uncertainty characterization methods such as computationally demanding Monte Carlo analyses and others methods restricted to linear model analyses. We present a unique application of a BDN to a groundwater modeling analysis of the hydrologic response of Assateague Island, Maryland to sea-level rise. Using both input and output variables of the modeled groundwater response to different sea-level (SLR) rise scenarios, the BDN predicts the probability of changes in the depth to fresh water, which exerts an important influence on physical and biological island evolution. Input variables included barrier-island width, maximum island elevation, and aquifer recharge. The variability of these inputs and their corresponding outputs are sampled along cross sections in a single model run to form an ensemble of input/output pairs. The BDN outputs, which are the posterior distributions of water table conditions for the sea-level rise scenarios, are evaluated through error analysis and cross-validation to assess both fit to training data and predictive power. The key benefit for using BDNs in groundwater modeling analyses is that they provide a method for distilling complex model results into predictions with associated uncertainty, which is useful to decision makers. Future efforts incorporate

  15. A Decision-Making Model Applied to Career Counseling.

    Science.gov (United States)

    Olson, Christine; And Others

    1990-01-01

    A four-component model for career decision-making counseling relates each component to assessment questions and appropriate intervention strategies. The components are (1) conceptualization (definition of the problem); (2) enlargement of response repertoire (generation of alternatives); (3) identification of discriminative stimuli (consequences of…

  16. A Behavioral Decision Making Modeling Approach Towards Hedging Services

    NARCIS (Netherlands)

    Pennings, J.M.E.; Candel, M.J.J.M.; Egelkraut, T.M.

    2003-01-01

    This paper takes a behavioral approach toward the market for hedging services. A behavioral decision-making model is developed that provides insight into how and why owner-managers decide the way they do regarding hedging services. Insight into those choice processes reveals information needed by fi

  17. Climate Modeling and Analysis with Decision Makers in Mind

    Science.gov (United States)

    Jones, A. D.; Jagannathan, K.; Calvin, K. V.; Lamarque, J. F.; Ullrich, P. A.

    2016-12-01

    There is a growing need for information about future climate conditions to support adaptation planning across a wide range of sectors and stakeholder communities. However, our principal tools for understanding future climate - global Earth system models - were not developed with these user needs in mind, nor have we developed transparent methods for evaluating and communicating the credibility of various climate information products with respect to the climate characteristics that matter most to decision-makers. Several recent community engagements have identified a need for "co-production" of knowledge among stakeholders and scientists. Here we highlight some of the barriers to communication and collaboration that must be overcome to improve the dialogue among researchers and climate adaptation practitioners in a meaningful way. Solutions to this challenge are two-fold: 1) new institutional arrangements and collaborative mechanisms designed to improve coordination and understanding among communities, and 2) a research agenda that explicitly incorporates stakeholder needs into model evaluation, development, and experimental design. We contrast the information content in global-scale model evaluation exercises with that required for in specific decision contexts, such as long-term agricultural management decisions. Finally, we present a vision for advancing the science of model evaluation in the context of predicting decision-relevant hydroclimate regime shifts in North America.

  18. Shared decision making: a model for clinical practice

    NARCIS (Netherlands)

    Elwyn, G.; Frosch, D.; Thomson, R.; Joseph-Williams, N.; Lloyd, A.; Kinnersley, P.; Cording, E.; Tomson, D.; Dodd, C.; Rollnick, S.; Edwards, A.; Barry, M.

    2012-01-01

    The principles of shared decision making are well documented but there is a lack of guidance about how to accomplish the approach in routine clinical practice. Our aim here is to translate existing conceptual descriptions into a three-step model that is practical, easy to remember, and can act as a

  19. Shared decision making: a model for clinical practice

    NARCIS (Netherlands)

    Elwyn, G.; Frosch, D.; Thomson, R.; Joseph-Williams, N.; Lloyd, A.; Kinnersley, P.; Cording, E.; Tomson, D.; Dodd, C.; Rollnick, S.; Edwards, A.; Barry, M.

    2012-01-01

    The principles of shared decision making are well documented but there is a lack of guidance about how to accomplish the approach in routine clinical practice. Our aim here is to translate existing conceptual descriptions into a three-step model that is practical, easy to remember, and can act as a

  20. The Integrated Decision Modeling System (IDMS) User’s Manual

    Science.gov (United States)

    1991-05-01

    AL-TP-1 991-0009 AD-A23 6 033 THE INTEGRATED DECISION MODELING SYSTEM (IDMS) USER’S MANUAL IJonathan C. Fast John N. Taylor Metrica , Incorporated...Looper 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) . PERFORMING ORGANIZATION REPORT NUMBER Metrica , Incorporated 8301 Broadway, Suite 215 San

  1. HYDRA: a decision support model for irrigation water management

    NARCIS (Netherlands)

    Jacucci, G.; Kabat, P.; Verrier, P.J.; Teixeira, J.L.; Steduto, P.; Bertanzon, G.; Giannerini, G.; Huygen, J.; Fernando, R.M.; Hooijer, A.A.; Simons, W.; Toller, G.; Tziallas, G.; Uhrik, C.; Broek, van den B.J.; Vera Munoz, J.; Yovchev, P.

    1995-01-01

    HYDRA introduces information modelling and decision-support systems (DSS) to farmers and authorities in European Mediterranean agriculture in order to improve irrigation practices at different levels. Key components of HYDRA-DSS are a hierarchical setof water balance and crop growth simulation

  2. Managing health care decisions and improvement through simulation modeling.

    Science.gov (United States)

    Forsberg, Helena Hvitfeldt; Aronsson, Håkan; Keller, Christina; Lindblad, Staffan

    2011-01-01

    Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.

  3. Rigorously testing multialternative decision field theory against random utility models.

    Science.gov (United States)

    Berkowitsch, Nicolas A J; Scheibehenne, Benjamin; Rieskamp, Jörg

    2014-06-01

    Cognitive models of decision making aim to explain the process underlying observed choices. Here, we test a sequential sampling model of decision making, multialternative decision field theory (MDFT; Roe, Busemeyer, & Townsend, 2001), on empirical grounds and compare it against 2 established random utility models of choice: the probit and the logit model. Using a within-subject experimental design, participants in 2 studies repeatedly choose among sets of options (consumer products) described on several attributes. The results of Study 1 showed that all models predicted participants' choices equally well. In Study 2, in which the choice sets were explicitly designed to distinguish the models, MDFT had an advantage in predicting the observed choices. Study 2 further revealed the occurrence of multiple context effects within single participants, indicating an interdependent evaluation of choice options and correlations between different context effects. In sum, the results indicate that sequential sampling models can provide relevant insights into the cognitive process underlying preferential choices and thus can lead to better choice predictions.

  4. Market orientation in the mental models of decision-makers

    DEFF Research Database (Denmark)

    Grunert, Klaus G.; Trondsen, Torbjørn; Campos, Emilio Gonzalo

    2010-01-01

    , decision makers exhibit overlap in their views of what drives their business. The pork chain appears dominated by a focus on efficiency, technology, and quality control, though it also acknowledges communication as important. The salmon chain places more emphasis on new product development and good......Purpose: This study determines whether predictions about different degrees of market orientation in two cross-border value chains also appear in the mental models of decision makers at two levels of these value chains. Design: The laddering method elicits mental models of actors in two value chains......: Norwegian salmon exported to Japan and Danish pork exported to Japan. The analysis of the mental models centers on potential overlap and linkages between actors in the value chain, including elements in the mental models that may relate to the actors' market orientation. Findings: In both value chains...

  5. Decision Tree Model for Non-Fatal Road Accident Injury

    Directory of Open Access Journals (Sweden)

    Fatin Ellisya Sapri

    2017-02-01

    Full Text Available Non-fatal road accident injury has become a great concern as it is associated with injury and sometimes leads to the disability of the victims. Hence, this study aims to develop a model that explains the factors that contribute to non-fatal road accident injury severity. A sample data of 350 non-fatal road accident cases of the year 2016 were obtained from Kota Bharu District Police Headquarters, Kelantan. The explanatory variables include road geometry, collision type, accident time, accident causes, vehicle type, age, airbag, and gender. The predictive data mining techniques of decision tree model and multinomial logistic regression were used to model non-fatal road accident injury severity. Based on accuracy rate, decision tree with CART algorithm was found to be more accurate as compared to the logistic regression model. The factors that significantly contribute to non-fatal traffic crashes injury severity are accident cause, road geometry, vehicle type, age and collision type.

  6. Kinetic models of collective decision-making in the presence of equality bias

    CERN Document Server

    Pareschi, Lorenzo; Zanella, Mattia

    2016-01-01

    We introduce and discuss kinetic models describing the influence of the competence in the evolution of decisions in a multi-agent system. The original exchange mechanism, which is based on the human tendency to compromise and change opinion through self-thinking, is here modified to include the role of the agents' competence. In particular, we take into account the agents' tendency to behave in the same way as if they were as good, or as bad, as their partner: the so-called equality bias. This occurred in a situation where a wide gap separated the competence of group members. We discuss the main properties of the kinetic models and numerically investigate some examples of collective decision under the influence of the equality bias. The results confirm that the equality bias leads the group to suboptimal decisions.

  7. Kinetic models of collective decision-making in the presence of equality bias

    Science.gov (United States)

    Pareschi, Lorenzo; Vellucci, Pierluigi; Zanella, Mattia

    2017-02-01

    We introduce and discuss kinetic models describing the influence of the competence in the evolution of decisions in a multi-agent system. The original exchange mechanism, which is based on the human tendency to compromise and change opinion through self-thinking, is here modified to include the role of the agents' competence. In particular, we take into account the agents' tendency to behave in the same way as if they were as good, or as bad, as their partner: the so-called equality bias. This occurred in a situation where a wide gap separated the competence of group members. We discuss the main properties of the kinetic models and numerically investigate some examples of collective decision under the influence of the equality bias. The results confirm that the equality bias leads the group to suboptimal decisions.

  8. An Integrated Decision Making Model for Evaluation of Concept Design

    Directory of Open Access Journals (Sweden)

    G. Green

    2004-01-01

    Full Text Available The Conceptual design phase generates various design concepts and these are then evaluated in order to identify the 'Best’ concept. Identifying the Best concept is important because much of the product life cycle cost is decided in this phase. Various evaluation techniques are performed so as to aid decision-making. Different criteria are weighted against concepts for the comparison. This paper describes the research being carried out at the University of Glasgow on design evaluation. It presents the Application of fuzzy logic for design evaluation and proposes an integrated decision-making model for design evaluation. This is a part of research project that aims at developing a computer tool for evaluation process to aid decision-making.

  9. Cognitive modeling and multi criteria decision making in macroeconomic analysis

    Directory of Open Access Journals (Sweden)

    Leonova Nina

    2014-01-01

    Full Text Available Decision making in macroeconomics belongs to the class of ill-structured tasks with strong external factors interdependence, a limited number of management tools and experts groups' subjectivity. This paper suggests a technique of macroeconomic analysis which includes methods of cognitive modeling for formalizing a problem situation and scenario generation as a basis of the typical multicriteria decision making task. In turn, for solving this task is suggested a method based on measuring the distance to the 'ideal' solution with determining importance of criteria by finding objective, common component of all values measured by experts groups. For extracting this 'commonality' means of factor analysis are used. Such an approach allows separating of the objective part in experts' value from a subjective one, while the technique at whole provides formalization of macroeconomic problems and substantiation of decision-making in macroeconomics.

  10. A decision-making process model of young online shoppers.

    Science.gov (United States)

    Lin, Chin-Feng; Wang, Hui-Fang

    2008-12-01

    Based on the concepts of brand equity, means-end chain, and Web site trust, this study proposes a novel model called the consumption decision-making process of adolescents (CDMPA) to understand adolescents' Internet consumption habits and behavioral intention toward particular sporting goods. The findings of the CDMPA model can help marketers understand adolescents' consumption preferences and habits for developing effective Internet marketing strategies.

  11. Cost modelling as decision support when locating manufacturing facilities

    Directory of Open Access Journals (Sweden)

    Christina Windmark

    2016-01-01

    Full Text Available This paper presents a methodology for cost estimation in developing decision supports for production location issues. The purpose is to provide a structured work procedure to be used by practitioners to derive the knowledge needed to make informed decisions on where to locate production. This paper present a special focus on how to integrate cost effects during the decision process. The work procedure and cost models were developed in close collaboration with a group of industrial partners. The result is a structure of cost estimation tools aligned to different steps in the work procedure. The cost models can facilitate both cost estimation for manufacturing a product under new preconditions, including support costs, and cost simulations to analyse the risks of wrong estimations and uncertainties in the input parameters. Future research aims to test the methodology in ongoing transfer projects to further understand difficulties in managing global production systems. In existing models and methods presented in the literature, cost is usually estimated on a too aggregated level to be suitable for decision support regarding production system design. The cost estimation methodology presented here provides new insights on cost driving factors related to the production system.

  12. An Integrated Model for Optimization Oriented Decision Aiding and Rule Based Decision Making in Fuzzy Environment

    OpenAIRE

    A. Yousefli; M. Ghazanfari; M. B. Abiri

    2014-01-01

    In this paper a fuzzy decision aid system is developed base on new concepts that presented in the field of fuzzy decision making in fuzzy environment (FDMFE). This framework aids decision makers to understand different circumstances of an uncertain problem that may occur in the future. Also, to keep decision maker from the optimization problem complexities, a decision support system, which can be replaced by optimization problem, is presented to make optimum or near optimum decisions without ...

  13. Acid deposition: decision framework. Volume 1. Description of conceptual framework and decision-tree models. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Balson, W.E.; Boyd, D.W.; North, D.W.

    1982-08-01

    Acid precipitation and dry deposition of acid materials have emerged as an important environmental issue affecting the electric utility industry. This report presents a framework for the analysis of decisions on acid deposition. The decision framework is intended as a means of summarizing scientific information and uncertainties on the relation between emissions from electric utilities and other sources, acid deposition, and impacts on ecological systems. The methodology for implementing the framework is that of decision analysis, which provides a quantitative means of analyzing decisions under uncertainty. The decisions of interest include reductions in sulfur oxide and other emissions thought to be precursors of acid deposition, mitigation of acid deposition impacts through means such as liming of waterways and soils, and choice of strategies for research. The report first gives an overview of the decision framework and explains the decision analysis methods with a simplified caricature example. The state of scientific information and the modeling assumptions for the framework are then discussed for the three main modules of the framework: emissions and control technologies; long-range transport and chemical conversion in the atmosphere; and ecological impacts. The report then presents two versions of a decision tree model that implements the decision framework. The basic decision tree addresses decisions on emissions control and mitigation in the immediate future and a decade hence, and it includes uncertainties in the long-range transport and ecological impacts. The research emphasis decision tree addresses the effect of research funding on obtaining new information as the basis for future decisions. Illustrative data and calculations using the decision tree models are presented.

  14. Critical Factors Influencing Decision to Adopt Human Resource Information System (HRIS) in Hospitals.

    Science.gov (United States)

    Alam, Md Golam Rabiul; Masum, Abdul Kadar Muhammad; Beh, Loo-See; Hong, Choong Seon

    2016-01-01

    The aim of this research is to explore factors influencing the management decisions to adopt human resource information system (HRIS) in the hospital industry of Bangladesh-an emerging developing country. To understand this issue, this paper integrates two prominent adoption theories-Human-Organization-Technology fit (HOT-fit) model and Technology-Organization-Environment (TOE) framework. Thirteen factors under four dimensions were investigated to explore their influence on HRIS adoption decisions in hospitals. Employing non-probability sampling method, a total of 550 copies of structured questionnaires were distributed among HR executives of 92 private hospitals in Bangladesh. Among the respondents, usable questionnaires were 383 that suggesting a valid response rate of 69.63%. We classify the sample into 3 core groups based on the HRIS initial implementation, namely adopters, prospectors, and laggards. The obtained results specify 5 most critical factors i.e. IT infrastructure, top management support, IT capabilities of staff, perceived cost, and competitive pressure. Moreover, the most significant dimension is technological dimension followed by organisational, human, and environmental among the proposed 4 dimensions. Lastly, the study found existence of significant differences in all factors across different adopting groups. The study results also expose constructive proposals to researchers, hospitals, and the government to enhance the likelihood of adopting HRIS. The present study has important implications in understanding HRIS implementation in developing countries.

  15. Toward an operational model of decision making, emotional regulation, and mental health impact.

    Science.gov (United States)

    Collura, Thomas Francis; Zalaquett, Ronald P; Bonnstetter, Carlos Joyce; Chatters, Seria J

    2014-01-01

    Current brain research increasingly reveals the underlying mechanisms and processes of human behavior, cognition, and emotion. In addition to being of interest to a wide range of scientists, educators, and professionals, as well as laypeople, brain-based models are of particular value in a clinical setting. Psychiatrists, psychologists, counselors, and other mental health professionals are in need of operational models that integrate recent findings in the physical, cognitive, and emotional domains, and offer a common language for interdisciplinary understanding and communication. Based on individual traits, predispositions, and responses to stimuli, we can begin to identify emotional and behavioral pathways and mental processing patterns. The purpose of this article is to present a brain-path activation model to understand individual differences in decision making and psychopathology. The first section discusses the role of frontal lobe electroencephalography (EEG) asymmetry, summarizes state- and trait-based models of decision making, and provides a more complex analysis that supplements the traditional simple left-right brain model. Key components of the new model are the introduction of right hemisphere parallel and left hemisphere serial scanning in rendering decisions, and the proposition of pathways that incorporate both past experiences as well as future implications into the decision process. Main attributes of each decision-making mechanism are provided. The second section applies the model within the realm of clinical mental health as a tool to understand specific human behavior and pathology. Applications include general and chronic anxiety, depression, paranoia, risk taking, and the pathways employed when well-functioning operational integration is observed. Finally, specific applications such as meditation and mindfulness are offered to facilitate positive functioning.

  16. Exploring Effective Decision Making through Human-Centered and Computational Intelligence Methods

    Energy Technology Data Exchange (ETDEWEB)

    Han, Kyungsik; Cook, Kristin A.; Shih, Patrick C.

    2016-06-13

    Decision-making has long been studied to understand a psychological, cognitive, and social process of selecting an effective choice from alternative options. Its studies have been extended from a personal level to a group and collaborative level, and many computer-aided decision-making systems have been developed to help people make right decisions. There has been significant research growth in computational aspects of decision-making systems, yet comparatively little effort has existed in identifying and articulating user needs and requirements in assessing system outputs and the extent to which human judgments could be utilized for making accurate and reliable decisions. Our research focus is decision-making through human-centered and computational intelligence methods in a collaborative environment, and the objectives of this position paper are to bring our research ideas to the workshop, and share and discuss ideas.

  17. Robust Decision-making Applied to Model Selection

    Energy Technology Data Exchange (ETDEWEB)

    Hemez, Francois M. [Los Alamos National Laboratory

    2012-08-06

    The scientific and engineering communities are relying more and more on numerical models to simulate ever-increasingly complex phenomena. Selecting a model, from among a family of models that meets the simulation requirements, presents a challenge to modern-day analysts. To address this concern, a framework is adopted anchored in info-gap decision theory. The framework proposes to select models by examining the trade-offs between prediction accuracy and sensitivity to epistemic uncertainty. The framework is demonstrated on two structural engineering applications by asking the following question: Which model, of several numerical models, approximates the behavior of a structure when parameters that define each of those models are unknown? One observation is that models that are nominally more accurate are not necessarily more robust, and their accuracy can deteriorate greatly depending upon the assumptions made. It is posited that, as reliance on numerical models increases, establishing robustness will become as important as demonstrating accuracy.

  18. Markov decision processes and the belief-desire-intention model

    CERN Document Server

    Simari, Gerardo I

    2011-01-01

    In this work, we provide a treatment of the relationship between two models that have been widely used in the implementation of autonomous agents: the Belief DesireIntention (BDI) model and Markov Decision Processes (MDPs). We start with an informal description of the relationship, identifying the common features of the two approaches and the differences between them. Then we hone our understanding of these differences through an empirical analysis of the performance of both models on the TileWorld testbed. This allows us to show that even though the MDP model displays consistently better beha

  19. Neuro-Based Artificial Intelligence Model for Loan Decisions

    Directory of Open Access Journals (Sweden)

    Shorouq F. Eletter

    2010-01-01

    Full Text Available Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpropagation learning algorithm was used to build up the proposed model. Results: Different representative cases of loan applications were considered based on the guidelines of different banks in Jordan, to validate the neural network model. Conclusion: The results indicated that artificial neural networks are a successful technology that can be used in loan application evaluation in the Jordanian commercial banks.

  20. Dynamic Decision Making for Graphical Models Applied to Oil Exploration

    CERN Document Server

    Martinelli, Gabriele; Hauge, Ragnar

    2012-01-01

    We present a framework for sequential decision making in problems described by graphical models. The setting is given by dependent discrete random variables with associated costs or revenues. In our examples, the dependent variables are the potential outcomes (oil, gas or dry) when drilling a petroleum well. The goal is to develop an optimal selection strategy that incorporates a chosen utility function within an approximated dynamic programming scheme. We propose and compare different approximations, from simple heuristics to more complex iterative schemes, and we discuss their computational properties. We apply our strategies to oil exploration over multiple prospects modeled by a directed acyclic graph, and to a reservoir drilling decision problem modeled by a Markov random field. The results show that the suggested strategies clearly improve the simpler intuitive constructions, and this is useful when selecting exploration policies.

  1. An Agent-Based Model of Farmer Decision Making in Jordan

    Science.gov (United States)

    Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

    2016-04-01

    We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

  2. Devaluation and sequential decisions: linking goal-directed and model-based behaviour

    Directory of Open Access Journals (Sweden)

    Eva eFriedel

    2014-08-01

    Full Text Available In experimental psychology different experiments have been developed to assess goal–directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed versus habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favour of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans.

  3. Devaluation and sequential decisions: linking goal-directed and model-based behavior.

    Science.gov (United States)

    Friedel, Eva; Koch, Stefan P; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian

    2014-01-01

    In experimental psychology different experiments have been developed to assess goal-directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans.

  4. Regulator Loss Functions and Hierarchical Modeling for Safety Decision Making.

    Science.gov (United States)

    Hatfield, Laura A; Baugh, Christine M; Azzone, Vanessa; Normand, Sharon-Lise T

    2017-07-01

    Regulators must act to protect the public when evidence indicates safety problems with medical devices. This requires complex tradeoffs among risks and benefits, which conventional safety surveillance methods do not incorporate. To combine explicit regulator loss functions with statistical evidence on medical device safety signals to improve decision making. In the Hospital Cost and Utilization Project National Inpatient Sample, we select pediatric inpatient admissions and identify adverse medical device events (AMDEs). We fit hierarchical Bayesian models to the annual hospital-level AMDE rates, accounting for patient and hospital characteristics. These models produce expected AMDE rates (a safety target), against which we compare the observed rates in a test year to compute a safety signal. We specify a set of loss functions that quantify the costs and benefits of each action as a function of the safety signal. We integrate the loss functions over the posterior distribution of the safety signal to obtain the posterior (Bayes) risk; the preferred action has the smallest Bayes risk. Using simulation and an analysis of AMDE data, we compare our minimum-risk decisions to a conventional Z score approach for classifying safety signals. The 2 rules produced different actions for nearly half of hospitals (45%). In the simulation, decisions that minimize Bayes risk outperform Z score-based decisions, even when the loss functions or hierarchical models are misspecified. Our method is sensitive to the choice of loss functions; eliciting quantitative inputs to the loss functions from regulators is challenging. A decision-theoretic approach to acting on safety signals is potentially promising but requires careful specification of loss functions in consultation with subject matter experts.

  5. Aggregation of Environmental Model Data for Decision Support

    Science.gov (United States)

    Alpert, J. C.

    2013-12-01

    Weather forecasts and warnings must be prepared and then delivered so as to reach their intended audience in good time to enable effective decision-making. An effort to mitigate these difficulties was studied at a Workshop, 'Sustaining National Meteorological Services - Strengthening WMO Regional and Global Centers' convened, June , 2013, by the World Bank, WMO and the US National Weather Service (NWS). The skill and accuracy of atmospheric forecasts from deterministic models have increased and there are now ensembles of such models that improve decisions to protect life, property and commerce. The NWS production of numerical weather prediction products result in model output from global and high resolution regional ensemble forecasts. Ensembles are constructed by changing the initial conditions to make a 'cloud' of forecasts that attempt to span the space of possible atmospheric realizations which can quantify not only the most likely forecast, but also the uncertainty. This has led to an unprecedented increase in data production and information content from higher resolution, multi-model output and secondary calculations. One difficulty is to obtain the needed subset of data required to estimate the probability of events, and report the information. The calibration required to reliably estimate the probability of events, and honing of threshold adjustments to reduce false alarms for decision makers is also needed. To meet the future needs of the ever-broadening user community and address these issues on a national and international basis, the weather service implemented the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS provides real-time and retrospective format independent access to climate, ocean and weather model data and delivers high availability content services as part of NOAA's official real time data dissemination at its new NCWCP web operations center. An important aspect of the server's abilities is to aggregate the matrix of

  6. The Cognitive Complexity in Modelling the Group Decision Process

    Directory of Open Access Journals (Sweden)

    Barna Iantovics

    2010-06-01

    Full Text Available The paper investigates for some basic contextual factors (such
    us the problem complexity, the users' creativity and the problem space complexity the cognitive complexity associated with modelling the group decision processes (GDP in e-meetings. The analysis is done by conducting a socio-simulation experiment for an envisioned collaborative software tool that acts as a stigmergic environment for modelling the GDP. The simulation results revels some interesting design guidelines for engineering some contextual functionalities that minimize the cognitive complexity associated with modelling the GDP.

  7. A Product Development Decision Model for Cockpit Weather Information System

    Science.gov (United States)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin; Johnson, Edward J., Jr. (Technical Monitor)

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

  8. A Product Development Decision Model for Cockpit Weather Information Systems

    Science.gov (United States)

    Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin

    2003-01-01

    There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

  9. A Soft Computing Model for Physicians' Decision Process

    CERN Document Server

    Biswas, Siddharths Sankar

    2010-01-01

    In this paper the author presents a kind of Soft Computing Technique, mainly an application of fuzzy set theory of Prof. Zadeh [16], on a problem of Medical Experts Systems. The choosen problem is on design of a physician's decision model which can take crisp as well as fuzzy data as input, unlike the traditional models. The author presents a mathematical model based on fuzzy set theory for physician aided evaluation of a complete representation of information emanating from the initial interview including patient past history, present symptoms, and signs observed upon physical examination and results of clinical and diagnostic tests.

  10. Modeling and Testing Landslide Hazard Using Decision Tree

    Directory of Open Access Journals (Sweden)

    Mutasem Sh. Alkhasawneh

    2014-01-01

    Full Text Available This paper proposes a decision tree model for specifying the importance of 21 factors causing the landslides in a wide area of Penang Island, Malaysia. These factors are vegetation cover, distance from the fault line, slope angle, cross curvature, slope aspect, distance from road, geology, diagonal length, longitude curvature, rugosity, plan curvature, elevation, rain perception, soil texture, surface area, distance from drainage, roughness, land cover, general curvature, tangent curvature, and profile curvature. Decision tree models are used for prediction, classification, and factors importance and are usually represented by an easy to interpret tree like structure. Four models were created using Chi-square Automatic Interaction Detector (CHAID, Exhaustive CHAID, Classification and Regression Tree (CRT, and Quick-Unbiased-Efficient Statistical Tree (QUEST. Twenty-one factors were extracted using digital elevation models (DEMs and then used as input variables for the models. A data set of 137570 samples was selected for each variable in the analysis, where 68786 samples represent landslides and 68786 samples represent no landslides. 10-fold cross-validation was employed for testing the models. The highest accuracy was achieved using Exhaustive CHAID (82.0% compared to CHAID (81.9%, CRT (75.6%, and QUEST (74.0% model. Across the four models, five factors were identified as most important factors which are slope angle, distance from drainage, surface area, slope aspect, and cross curvature.

  11. Model Checking with Edge-Valued Decision Diagrams

    Science.gov (United States)

    Roux, Pierre; Siminiceanu, Radu I.

    2010-01-01

    We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library. We provide efficient algorithms for manipulating EVMDDs and review the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi- Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools. Compared to the CUDD package, our tool is several orders of magnitude faster

  12. New models for decision making in moral theology.

    Science.gov (United States)

    Lauer, E F

    1986-01-01

    The way that the Christian tradition faces moral issues is being reshaped. Rather than focusing solely on Scripture and tradition as the basis for resolving ethical issues, decision makers should investigate human experience as well, some contemporary theologians recommend. In contrast to a traditional notion of natural law, which analyzes "human nature," the revisionist approach analyzes human experiences to discover what is authentic in them. This process looks not only at the physical structure of an act but also at its intentionality and its effect on the parties involved. Absolute material norms do not exist, according to the revisionist school. Instead one must examine an act's effects on a person's relationship to God, to others, to the physical world, and to oneself to determine whether it is morally right or wrong. Although this theological trend could be disconcerting to those who serve on ethics committees--since it does not rely on clear-cut rules--and may make decision making more difficult, its value lies in its potential to bring Christians closer to a divine understanding of reality.

  13. Multinational Parent Companies' Influence over Human Resource Decisions of Affiliates: U.S. Firms in Mexico

    OpenAIRE

    Zaida L. Martinez; David A Ricks

    1989-01-01

    This study provides empirical evidence for the relationship between the degree of influence U.S. parent companies have over the human resource decisions of their Mexican affiliates and the affiliates' resource dependencies on the parent company. Both wholly-owned and Joint venture affiliates are examined. Resource dependence was the factor most closely related to parent influence over affiliate human resource decisions. The importance of an affiliate to a parent company, the nationality of af...

  14. The Insertion of Human Factors Concerns into NextGen Programmatic Decisions

    Science.gov (United States)

    Beard, Bettina L.; Holbrook, Jon Brian; Seely, Rachel

    2013-01-01

    Since the costs of proposed improvements in air traffic management exceed available funding, FAA decision makers must select and prioritize what actually gets implemented. We discuss a set of methods to help forecast operational and human performance issues and benefits before new automation is introduced. This strategy could minimize the impact of politics, assist decision makers in selecting and prioritizing potential improvements, make the process more transparent and strengthen the link between the engineering and human factors domains.

  15. Computer simulation of leadership, consensus decision making and collective behaviour in humans.

    Science.gov (United States)

    Wu, Song; Sun, Quanbin

    2014-01-01

    The aim of this study is to evaluate the reliability of a crowd simulation model developed by the authors by reproducing Dyer et al.'s experiments (published in Philosophical Transactions in 2009) on human leadership and consensus decision making in a computer-based environment. The theoretical crowd model of the simulation environment is presented, and its results are compared and analysed against Dyer et al.'s original experiments. It is concluded that the simulation results are largely consistent with the experiments, which demonstrates the reliability of the crowd model. Furthermore, the simulation data also reveals several additional new findings, namely: 1) the phenomena of sacrificing accuracy to reach a quicker consensus decision found in ants colonies was also discovered in the simulation; 2) the ability of reaching consensus in groups has a direct impact on the time and accuracy of arriving at the target position; 3) the positions of the informed individuals or leaders in the crowd could have significant impact on the overall crowd movement; and 4) the simulation also confirmed Dyer et al.'s anecdotal evidence of the proportion of the leadership in large crowds and its effect on crowd movement. The potential applications of these findings are highlighted in the final discussion of this paper.

  16. Computer simulation of leadership, consensus decision making and collective behaviour in humans.

    Directory of Open Access Journals (Sweden)

    Song Wu

    Full Text Available The aim of this study is to evaluate the reliability of a crowd simulation model developed by the authors by reproducing Dyer et al.'s experiments (published in Philosophical Transactions in 2009 on human leadership and consensus decision making in a computer-based environment. The theoretical crowd model of the simulation environment is presented, and its results are compared and analysed against Dyer et al.'s original experiments. It is concluded that the simulation results are largely consistent with the experiments, which demonstrates the reliability of the crowd model. Furthermore, the simulation data also reveals several additional new findings, namely: 1 the phenomena of sacrificing accuracy to reach a quicker consensus decision found in ants colonies was also discovered in the simulation; 2 the ability of reaching consensus in groups has a direct impact on the time and accuracy of arriving at the target position; 3 the positions of the informed individuals or leaders in the crowd could have significant impact on the overall crowd movement; and 4 the simulation also confirmed Dyer et al.'s anecdotal evidence of the proportion of the leadership in large crowds and its effect on crowd movement. The potential applications of these findings are highlighted in the final discussion of this paper.

  17. USING THE SOFTWARE MICROSOFT OFFICE EXCEL FOR FINANCIAL MODELING DECISION

    Directory of Open Access Journals (Sweden)

    Bălăc escu Aniela

    2009-05-01

    Full Text Available The use of the software package is today indispensable for modeling of financial decisions. Business organizations will invariably make greater demands of the software than individual users. Excel is an option along with other software applications tailored to the market, and bespoke (in-house software packages. It should be noted that Excel is the leader in the market and as such does set a benchmark.

  18. Reverse engineering cellular decisions for hybrid reconfigurable network modeling

    Science.gov (United States)

    Blair, Howard A.; Saranak, Jureepan; Foster, Kenneth W.

    2011-06-01

    Cells as microorganisms and within multicellular organisms make robust decisions. Knowing how these complex cells make decisions is essential to explain, predict or mimic their behavior. The discovery of multi-layer multiple feedback loops in the signaling pathways of these modular hybrid systems suggests their decision making is sophisticated. Hybrid systems coordinate and integrate signals of various kinds: discrete on/off signals, continuous sensory signals, and stochastic and continuous fluctuations to regulate chemical concentrations. Such signaling networks can form reconfigurable networks of attractors and repellors giving them an extra level of organization that has resilient decision making built in. Work on generic attractor and repellor networks and on the already identified feedback networks and dynamic reconfigurable regulatory topologies in biological cells suggests that biological systems probably exploit such dynamic capabilities. We present a simple behavior of the swimming unicellular alga Chlamydomonas that involves interdependent discrete and continuous signals in feedback loops. We show how to rigorously verify a hybrid dynamical model of a biological system with respect to a declarative description of a cell's behavior. The hybrid dynamical systems we use are based on a unification of discrete structures and continuous topologies developed in prior work on convergence spaces. They involve variables of discrete and continuous types, in the sense of type theory in mathematical logic. A unification such as afforded by convergence spaces is necessary if one wants to take account of the affect of the structural relationships within each type on the dynamics of the system.

  19. Modelling Framework to Support Decision-Making in Manufacturing Enterprises

    Directory of Open Access Journals (Sweden)

    Tariq Masood

    2013-01-01

    Full Text Available Systematic model-driven decision-making is crucial to design, engineer, and transform manufacturing enterprises (MEs. Choosing and applying the best philosophies and techniques is challenging as most MEs deploy complex and unique configurations of process-resource systems and seek economies of scope and scale in respect of changing and distinctive product flows. This paper presents a novel systematic enhanced integrated modelling framework to facilitate transformation of MEs, which is centred on CIMOSA. Application of the new framework in an automotive industrial case study is also presented. The following new contributions to knowledge are made: (1 an innovative structured framework that can support various decisions in design, optimisation, and control to reconfigure MEs; (2 an enriched and generic process modelling approach with capability to represent both static and dynamic aspects of MEs; and (3 an automotive industrial case application showing benefits in terms of reduced lead time and cost with improved responsiveness of process-resource system with a special focus on PPC. It is anticipated that the new framework is not limited to only automotive industry but has a wider scope of application. Therefore, it would be interesting to extend its testing with different configurations and decision-making levels.

  20. Human Information Processing Guidelines for Decision-Aiding Displays.

    Science.gov (United States)

    1981-12-01

    5 4. Pachella, R. G. "The Interpretation of Reaction Time in Information Processing Research." In B. Kantowitz (Ed.). Human Information Pro- cessing... Kantowitz (Ed.). Human Information Proces- sing: Tutorials in Performance and Cognition, Hillsdale, New Jersey: Lawrence Erlbaum Associates, 1974. 65...Finite Number of Inputs." In B. Kantowitz (Ed.). Human Information Processing: Tutorials in Performance and Cognition, Hillsdale, New Jersey: Lawrence

  1. Time to decide: Diurnal variations on the speed and quality of human decisions.

    Science.gov (United States)

    Leone, María Juliana; Fernandez Slezak, Diego; Golombek, Diego; Sigman, Mariano

    2017-01-01

    Human behavior and physiology exhibit diurnal fluctuations. These rhythms are entrained by light and social cues, with vast individual differences in the phase of entrainment - referred as an individual's chronotype - ranging in a continuum between early larks and late owls. Understanding whether decision-making in real-life situations depends on the relation between time of the day and an individual's diurnal preferences has both practical and theoretical implications. However, answering this question has remained elusive because of the difficulty of measuring precisely the quality of a decision in real-life scenarios. Here we investigate diurnal variations in decision-making as a function of an individual's chronotype capitalizing on a vast repository of human decisions: online chess servers. In a chess game, every player has to make around 40 decisions using a finite time budget and both the time and quality of each decision can be accurately determined. We found reliable diurnal rhythms in activity and decision-making policy. During the morning, players adopt a prevention focus policy (slower and more accurate decisions) which is later modified to a promotion focus (faster but less accurate decisions), without daily changes in performance. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Effects of stochastic interest rates in decision making under risk: A Markov decision process model for forest management

    Science.gov (United States)

    Mo Zhou; Joseph Buongiorno

    2011-01-01

    Most economic studies of forest decision making under risk assume a fixed interest rate. This paper investigated some implications of this stochastic nature of interest rates. Markov decision process (MDP) models, used previously to integrate stochastic stand growth and prices, can be extended to include variable interest rates as well. This method was applied to...

  3. Market orientation in the mental models of decision-makers

    DEFF Research Database (Denmark)

    Grunert, Klaus G.; Trondsen, Torbjørn; Campos, Emilio Gonzalo

    2010-01-01

    : Norwegian salmon exported to Japan and Danish pork exported to Japan. The analysis of the mental models centers on potential overlap and linkages between actors in the value chain, including elements in the mental models that may relate to the actors' market orientation. Findings: In both value chains......Purpose: This study determines whether predictions about different degrees of market orientation in two cross-border value chains also appear in the mental models of decision makers at two levels of these value chains. Design: The laddering method elicits mental models of actors in two value chains...... in promoting the market orientation of value chains. Originality: This article offers three novel ideas: using the concept of mental models as a possible mediator between factors that influence the degree of market orientation and market-oriented activity; using a laddering method to elicit mental models...

  4. Markov chain decision model for urinary incontinence procedures.

    Science.gov (United States)

    Kumar, Sameer; Ghildayal, Nidhi; Ghildayal, Neha

    2017-03-13

    Purpose Urinary incontinence (UI) is a common chronic health condition, a problem specifically among elderly women that impacts quality of life negatively. However, UI is usually viewed as likely result of old age, and as such is generally not evaluated or even managed appropriately. Many treatments are available to manage incontinence, such as bladder training and numerous surgical procedures such as Burch colposuspension and Sling for UI which have high success rates. The purpose of this paper is to analyze which of these popular surgical procedures for UI is effective. Design/methodology/approach This research employs randomized, prospective studies to obtain robust cost and utility data used in the Markov chain decision model for examining which of these surgical interventions is more effective in treating women with stress UI based on two measures: number of quality adjusted life years (QALY) and cost per QALY. Treeage Pro Healthcare software was employed in Markov decision analysis. Findings Results showed the Sling procedure is a more effective surgical intervention than the Burch. However, if a utility greater than certain utility value, for which both procedures are equally effective, is assigned to persistent incontinence, the Burch procedure is more effective than the Sling procedure. Originality/value This paper demonstrates the efficacy of a Markov chain decision modeling approach to study the comparative effectiveness analysis of available treatments for patients with UI, an important public health issue, widely prevalent among elderly women in developed and developing countries. This research also improves upon other analyses using a Markov chain decision modeling process to analyze various strategies for treating UI.

  5. LATEST: A model of saccadic decisions in space and time.

    Science.gov (United States)

    Tatler, Benjamin W; Brockmole, James R; Carpenter, R H S

    2017-04-01

    Many of our actions require visual information, and for this it is important to direct the eyes to the right place at the right time. Two or three times every second, we must decide both when and where to direct our gaze. Understanding these decisions can reveal the moment-to-moment information priorities of the visual system and the strategies for information sampling employed by the brain to serve ongoing behavior. Most theoretical frameworks and models of gaze control assume that the spatial and temporal aspects of fixation point selection depend on different mechanisms. We present a single model that can simultaneously account for both when and where we look. Underpinning this model is the theoretical assertion that each decision to move the eyes is an evaluation of the relative benefit expected from moving the eyes to a new location compared with that expected by continuing to fixate the current target. The eyes move when the evidence that favors moving to a new location outweighs that favoring staying at the present location. Our model provides not only an account of when the eyes move, but also what will be fixated. That is, an analysis of saccade timing alone enables us to predict where people look in a scene. Indeed our model accounts for fixation selection as well as (and often better than) current computational models of fixation selection in scene viewing. (PsycINFO Database Record

  6. Economic decision making and the application of nonparametric prediction models

    Science.gov (United States)

    Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

    2008-01-01

    Sustained increases in energy prices have focused attention on gas resources in low-permeability shale or in coals that were previously considered economically marginal. Daily well deliverability is often relatively small, although the estimates of the total volumes of recoverable resources in these settings are often large. Planning and development decisions for extraction of such resources must be areawide because profitable extraction requires optimization of scale economies to minimize costs and reduce risk. For an individual firm, the decision to enter such plays depends on reconnaissance-level estimates of regional recoverable resources and on cost estimates to develop untested areas. This paper shows how simple nonparametric local regression models, used to predict technically recoverable resources at untested sites, can be combined with economic models to compute regional-scale cost functions. The context of the worked example is the Devonian Antrim-shale gas play in the Michigan basin. One finding relates to selection of the resource prediction model to be used with economic models. Models chosen because they can best predict aggregate volume over larger areas (many hundreds of sites) smooth out granularity in the distribution of predicted volumes at individual sites. This loss of detail affects the representation of economic cost functions and may affect economic decisions. Second, because some analysts consider unconventional resources to be ubiquitous, the selection and order of specific drilling sites may, in practice, be determined arbitrarily by extraneous factors. The analysis shows a 15-20% gain in gas volume when these simple models are applied to order drilling prospects strategically rather than to choose drilling locations randomly. Copyright ?? 2008 Society of Petroleum Engineers.

  7. Data acquisition in modeling using neural networks and decision trees

    Directory of Open Access Journals (Sweden)

    R. Sika

    2011-04-01

    Full Text Available The paper presents a comparison of selected models from area of artificial neural networks and decision trees in relation with actualconditions of foundry processes. The work contains short descriptions of used algorithms, their destination and method of data preparation,which is a domain of work of Data Mining systems. First part concerns data acquisition realized in selected iron foundry, indicating problems to solve in aspect of casting process modeling. Second part is a comparison of selected algorithms: a decision tree and artificial neural network, that is CART (Classification And Regression Trees and BP (Backpropagation in MLP (Multilayer Perceptron networks algorithms.Aim of the paper is to show an aspect of selecting data for modeling, cleaning it and reducing, for example due to too strong correlationbetween some of recorded process parameters. Also, it has been shown what results can be obtained using two different approaches:first when modeling using available commercial software, for example Statistica, second when modeling step by step using Excel spreadsheetbasing on the same algorithm, like BP-MLP. Discrepancy of results obtained from these two approaches originates from a priorimade assumptions. Mentioned earlier Statistica universal software package, when used without awareness of relations of technologicalparameters, i.e. without user having experience in foundry and without scheduling ranks of particular parameters basing on acquisition, can not give credible basis to predict the quality of the castings. Also, a decisive influence of data acquisition method has been clearly indicated, the acquisition should be conducted according to repetitive measurement and control procedures. This paper is based on about 250 records of actual data, for one assortment for 6 month period, where only 12 data sets were complete (including two that were used for validation of neural network and useful for creating a model. It is definitely too

  8. Decision Making in Rangelands: An Integrated Modeling Approach to Resilience and Change

    Science.gov (United States)

    Galvin, K. A.; Ojima, D. S.; Boone, R. B.

    2007-12-01

    Rangelands comprise approximately 25% of the earth's surface and these landscapes support more than 20 million people and most of the world's charismatic megafauna. Most of the people who live in these regions of the world herd domestic livestock and some do limited cultivation so they are dependent directly on the environment for their livelihoods. But change is rapidly changing the environments upon which these people depend through such factors as population pressures, land use and land tenure changes, climate variability, and policy changes which fragment their resources and thus their ability to earn a living. How can we understand change in this linked human-environment system? The study of complex biophysical and human systems can be greatly assisted by appropriate simulation models that integrate what is known about ecological and human decision-making processes. We have developed an integrated modeling system for Kajiado, Kenya where land use management decisions have implications for economics and the ecosystem. In this paper we look at how land use decisions, that is, livestock movement patterns have implications for societal economics and ecosystem services. Research that focuses on local behavior is important because it is at that level where fundamental decisions are made regarding events like extreme climate and changes such as land tenure policy and it is here where resilience is manifested. The notion that broad recommendation domains can be identified for a broad set of people and large regions coping with change is becoming increasingly hard to trust given the spatial and temporal heterogeneity of the systems we are looking at, and the complexity of the world we now live in. Why is this important? The only way the research community is going to make great progress in attaining objectives that do confer resilience (on social and ecological systems) is through much better targeting ability, a large part of which seem to be intimately entwined with

  9. A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making.

    Science.gov (United States)

    Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

    2017-01-01

    Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from

  10. A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

    Science.gov (United States)

    Prezenski, Sabine; Brechmann, André; Wolff, Susann; Russwinkel, Nele

    2017-01-01

    Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying cognitive processes from

  11. A Cognitive Modeling Approach to Strategy Formation in Dynamic Decision Making

    Directory of Open Access Journals (Sweden)

    Sabine Prezenski

    2017-08-01

    Full Text Available Decision-making is a high-level cognitive process based on cognitive processes like perception, attention, and memory. Real-life situations require series of decisions to be made, with each decision depending on previous feedback from a potentially changing environment. To gain a better understanding of the underlying processes of dynamic decision-making, we applied the method of cognitive modeling on a complex rule-based category learning task. Here, participants first needed to identify the conjunction of two rules that defined a target category and later adapt to a reversal of feedback contingencies. We developed an ACT-R model for the core aspects of this dynamic decision-making task. An important aim of our model was that it provides a general account of how such tasks are solved and, with minor changes, is applicable to other stimulus materials. The model was implemented as a mixture of an exemplar-based and a rule-based approach which incorporates perceptual-motor and metacognitive aspects as well. The model solves the categorization task by first trying out one-feature strategies and then, as a result of repeated negative feedback, switching to two-feature strategies. Overall, this model solves the task in a similar way as participants do, including generally successful initial learning as well as reversal learning after the change of feedback contingencies. Moreover, the fact that not all participants were successful in the two learning phases is also reflected in the modeling data. However, we found a larger variance and a lower overall performance of the modeling data as compared to the human data which may relate to perceptual preferences or additional knowledge and rules applied by the participants. In a next step, these aspects could be implemented in the model for a better overall fit. In view of the large interindividual differences in decision performance between participants, additional information about the underlying

  12. A Decision Model for Selecting Participants in Supply Chain

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    In order to satisfy the rapid changing requirements of customers, enterprises must cooperate with each other to form supply chain. The first and the most important stage in the forming of supply chain is the selection of participants. The article proposes a two-staged decision model to select partners. The first stage is the inter company comparison in each business process to select highefficiency candidate based on inside variables. The next stage is to analyse the combination of different candidates in order to select the most perfect partners according to a goal-programming model.

  13. Computational EEG modelling of decision making under ambiguity reveals spatio-temporal dynamics of outcome evaluation.

    Science.gov (United States)

    Jollans, Lee; Whelan, Robert; Venables, Louise; Turnbull, Oliver H; Cella, Matteo; Dymond, Simon

    2017-03-15

    Complex human cognition, such as decision-making under ambiguity, is reflected in dynamic spatio-temporal activity in the brain. Here, we combined event-related potentials with computational modelling of the time course of decision-making and outcome evaluation during the Iowa Gambling Task. Measures of choice probability generated using the Prospect Valence Learning Delta (PVL-Delta) model, in addition to objective trial outcomes (outcome magnitude and valence), were applied as regressors in a general linear model of the EEG signal. The resulting three-dimensional spatio-temporal characterization of task-related neural dynamics demonstrated that outcome valence, outcome magnitude, and PVL-Delta choice probability were expressed in distinctly separate event related potentials. Our findings showed that the P3 component was associated with an experience-based measure of outcome expectancy. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED).

    Science.gov (United States)

    Fontaine, Reid Griffith; Dodge, Kenneth A

    2006-11-01

    Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

  15. Pavement maintenance optimization model using Markov Decision Processes

    Science.gov (United States)

    Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

    2017-09-01

    This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

  16. The Dutch model for legalizing end-of-life decisions.

    Science.gov (United States)

    Kater, Loes

    2003-01-01

    The Dutch experience with euthanasia is used as a model for other countries for regulating end-of-life decisions. Several elements of the Dutch debate, for example the definition of euthanasia, are copied and imported to other debates. This paper studies the specific Dutch construction of regulating euthanasia and the concept of the requirements of prudent practice. The requirements of prudent practice embody the conditions for careful medical management in end-of-life decisions. It is argued that the requirements of prudent practice are a relatively acceptable way of regulating the Dutch practice of euthanasia as they are embedded in an elaborate network of relations, standards and values. As a consequence of this local character and the way the requirements of prudent practice relate to the Dutch practice of euthanasia it is difficult to simply transport them to other countries in order to regulate euthanasia.

  17. The Controlling Model as Management Support in Decision- Making

    Directory of Open Access Journals (Sweden)

    Berislav Bolfek

    2010-07-01

    Full Text Available business system to operate successfully and make profit, which represents the success criterion for each business system on the market. For managing the business result, the management of business systems needs different types of information on which numerous managerial decisions are based. That is why it is necessary to develop and set a Business System Controlling Model which would have the capability to transform available data into the information necessary for managerial decision-making. The above-mentioned model is prepared in such a way that the whole process of the transformation of the data into required information is carried out in two interconnected steps which have to be made in every single case and situation. However, there are a certain number of different activities within each step which do not have to be performed in every case. The forecast presented in the form of the Profit Forecast Procedure and the Liquidity Forecast Procedure represents the essence of the Business System Controlling Model. The Business System Controlling Model developed and set out in this paper should enable the business system management to evaluate future business activities, in addition to monitoring the past and present business activities. It is precisely the evaluation of the future business activities that, in today’s conditions of greater market globalization and internationalization, should help the business system management to control the business result in a better and easier way. In this way, the Business System Controlling Model represents a new tool in the sense of management support in making various business decisions.

  18. Evaluating the link between human resource management decisions and patient satisfaction with quality of care.

    Science.gov (United States)

    Oppel, Eva-Maria; Winter, Vera; Schreyögg, Jonas

    Patient satisfaction with quality of care is becoming increasingly important in the competitive hospital market. Simultaneously, the growing shortage of clinical staff poses a considerable challenge to ensuring a high quality of care. In this context, a question emerges regarding whether and how human resource management (HRM) might serve as a means to reduce staff shortage problems and to increase patient satisfaction. Although considerable efforts have been devoted to understanding the concepts of patient satisfaction and HRM, little is known about the interrelationships between these concepts or about the link between staff shortage problems and patients' satisfaction with quality of care. The aim of this study was to investigate the relationship between strategic human resource management (SHRM), staff shortage problems, and patients' satisfaction with care. Furthermore, we analyze how the HRM decision to fill short-term vacancies through temporary staffing affects patient satisfaction. We differentiate between physicians and nurses. We develop and empirically test a theoretical model. The data (n = 165) are derived from a survey on SHRM that was sent to 732 German hospitals and from a survey on patient satisfaction that comprises 436,848 patient satisfaction ratings. We use a structural equation modeling approach to test the model. The results indicate that SHRM significantly reduces staff shortage problems for both occupational groups. Having fewer physician shortage problems is significantly associated with higher levels of patient satisfaction, whereas this effect is not significant for nurses. Furthermore, the use of temporary staffing considerably reduces patients' satisfaction with care. Hospital managers are advised to consider the effects of HRM decisions on patients' satisfaction with care. In particular, investments in SHRM targeted at physicians have significantly positive effects on patient satisfaction, whereas the temporary staffing of physicians

  19. Decision and action planning signals in human posterior parietal cortex during delayed perceptual choices.

    Science.gov (United States)

    Tosoni, Annalisa; Corbetta, Maurizio; Calluso, Cinzia; Committeri, Giorgia; Pezzulo, Giovanni; Romani, G L; Galati, Gaspare

    2014-04-01

    During simple perceptual decisions, sensorimotor neurons in monkey fronto-parietal cortex represent a decision variable that guides the transformation of sensory evidence into a motor response, supporting the view that mechanisms for decision-making are closely embedded within sensorimotor structures. Within these structures, however, decision signals can be dissociated from motor signals, thus indicating that sensorimotor neurons can play multiple and independent roles in decision-making and action selection/planning. Here we used functional magnetic resonance imaging to examine whether response-selective human brain areas encode signals for decision-making or action planning during a task requiring an arbitrary association between face pictures (male vs. female) and specific actions (saccadic eye vs. hand pointing movements). The stimuli were gradually unmasked to stretch the time necessary for decision, thus maximising the temporal separation between decision and action planning. Decision-related signals were measured in parietal and motor/premotor regions showing a preference for the planning/execution of saccadic or pointing movements. In a parietal reach region, decision-related signals were specific for the stimulus category associated with its preferred pointing response. By contrast, a saccade-selective posterior intraparietal sulcus region carried decision-related signals even when the task required a pointing response. Consistent signals were observed in the motor/premotor cortex. Whole-brain analyses indicated that, in our task, the most reliable decision signals were found in the same neural regions involved in response selection. However, decision- and action-related signals within these regions can be dissociated. Differences between the parietal reach region and posterior intraparietal sulcus plausibly depend on their functional specificity rather than on the task structure. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons

  20. Modeling human color categorization

    NARCIS (Netherlands)

    van den Broek, Egon; Schouten, Th.E.; Kisters, P.M.F.

    2008-01-01

    A unique color space segmentation method is introduced. It is founded on features of human cognition, where 11 color categories are used in processing color. In two experiments, human subjects were asked to categorize color stimuli into these 11 color categories, which resulted in markers for a Colo

  1. Modeling human color categorization

    NARCIS (Netherlands)

    van den Broek, Egon; Schouten, Th.E.; Kisters, P.M.F.

    A unique color space segmentation method is introduced. It is founded on features of human cognition, where 11 color categories are used in processing color. In two experiments, human subjects were asked to categorize color stimuli into these 11 color categories, which resulted in markers for a

  2. Expanding business-to-business customer relationships : modeling the customer's upgrade decision

    NARCIS (Netherlands)

    Bolton, R.; Lemon, K.N.; Verhoef, P.C.

    2008-01-01

    This article develops a model of a business customer's decision to upgrade service contracts conditional on the decision to renew the contract. It proposes that the firm's upgrade decision is influenced by (1) decision-maker perceptions of the relationship with the supplier, (2) contract-level exper

  3. Expanding business-to-business customer relationships : modeling the customer's upgrade decision

    NARCIS (Netherlands)

    Bolton, R.; Lemon, K.N.; Verhoef, P.C.

    This article develops a model of a business customer's decision to upgrade service contracts conditional on the decision to renew the contract. It proposes that the firm's upgrade decision is influenced by (1) decision-maker perceptions of the relationship with the supplier, (2) contract-level

  4. Exploring the experiences of client involvement in medication decisions using a shared decision making model: results of a qualitative study.

    Science.gov (United States)

    Goscha, Richard; Rapp, Charles

    2015-04-01

    This qualitative study explored a newly introduced model of shared decision making (CommonGround) and how psychiatric medications were experienced by clients, prescribers, case managers and peer support staff. Of the twelve client subjects, six were highly engaged in shared decision-making and six were not. Five notable differences were found between the two groups including the presence of a goal, use of personal medicine, and the behavior of case managers and prescribers. Implications for a shared decision making model in psychiatry are discussed.

  5. A value model for evaluating homeland security decisions.

    Science.gov (United States)

    Keeney, Ralph L; von Winterfeldt, Detlof

    2011-09-01

    One of the most challenging tasks of homeland security policymakers is to allocate their limited resources to reduce terrorism risks cost effectively. To accomplish this task, it is useful to develop a comprehensive set of homeland security objectives, metrics to measure each objective, a utility function, and value tradeoffs relevant for making homeland security investments. Together, these elements form a homeland security value model. This article develops a homeland security value model based on literature reviews, a survey, and experience with building value models. The purposes of the article are to motivate the use of a value model for homeland security decision making and to illustrate its use to assess terrorism risks, assess the benefits of countermeasures, and develop a severity index for terrorism attacks. © 2011 Society for Risk Analysis.

  6. Knowledge model-based decision support system for maize management

    Institute of Scientific and Technical Information of China (English)

    GUO Yinqiao; ZHAO Chuande; WANG Wenxin; LI Cundong

    2007-01-01

    Based on the relationship between crops and circumstances,a dynamic knowledge model for maize management with wide applicability was developed using the system method and mathematical modeling technique.With soft component characteristics incorporated,a component and digital knowledge model-based decision support system for maize management was established on the Visual C++platform.This system realized six major functions:target yield calculation,design of pre-sowing plan,prediction of regular indices,real-time management control,expert knowledge reference and system administration.Cases were studied on the target yield knowledge model with data sets that include different eco-sites,yield levels of the last three years,and fertilizer and water management levels.The results indicated that this system overcomes the shortcomings of traditional expert systems and planting patterns,such as sitespecific conditions and narrow applicability,and can be used more under different conditions and environments.This system provides a scientific knowledge system and a broad decision-making tool for maize management.

  7. Framework for Human Health Risk Assessment to Inform Decision Making

    Science.gov (United States)

    The purpose of this document is to describe a Framework for conducting human health risk assessments that are responsive to the needs of decision‐making processes in the U.S. Environmental Protection Agency (EPA).

  8. Genomic responses in mouse models poorly mimic human inflammatory diseases.

    Science.gov (United States)

    Seok, Junhee; Warren, H Shaw; Cuenca, Alex G; Mindrinos, Michael N; Baker, Henry V; Xu, Weihong; Richards, Daniel R; McDonald-Smith, Grace P; Gao, Hong; Hennessy, Laura; Finnerty, Celeste C; López, Cecilia M; Honari, Shari; Moore, Ernest E; Minei, Joseph P; Cuschieri, Joseph; Bankey, Paul E; Johnson, Jeffrey L; Sperry, Jason; Nathens, Avery B; Billiar, Timothy R; West, Michael A; Jeschke, Marc G; Klein, Matthew B; Gamelli, Richard L; Gibran, Nicole S; Brownstein, Bernard H; Miller-Graziano, Carol; Calvano, Steve E; Mason, Philip H; Cobb, J Perren; Rahme, Laurence G; Lowry, Stephen F; Maier, Ronald V; Moldawer, Lyle L; Herndon, David N; Davis, Ronald W; Xiao, Wenzhong; Tompkins, Ronald G

    2013-02-26

    A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R(2) between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases.

  9. Genomic responses in mouse models poorly mimic human inflammatory diseases

    Science.gov (United States)

    Seok, Junhee; Warren, H. Shaw; Cuenca, Alex G.; Mindrinos, Michael N.; Baker, Henry V.; Xu, Weihong; Richards, Daniel R.; McDonald-Smith, Grace P.; Gao, Hong; Hennessy, Laura; Finnerty, Celeste C.; López, Cecilia M.; Honari, Shari; Moore, Ernest E.; Minei, Joseph P.; Cuschieri, Joseph; Bankey, Paul E.; Johnson, Jeffrey L.; Sperry, Jason; Nathens, Avery B.; Billiar, Timothy R.; West, Michael A.; Jeschke, Marc G.; Klein, Matthew B.; Gamelli, Richard L.; Gibran, Nicole S.; Brownstein, Bernard H.; Miller-Graziano, Carol; Calvano, Steve E.; Mason, Philip H.; Cobb, J. Perren; Rahme, Laurence G.; Lowry, Stephen F.; Maier, Ronald V.; Moldawer, Lyle L.; Herndon, David N.; Davis, Ronald W.; Xiao, Wenzhong; Tompkins, Ronald G.; Abouhamze, Amer; Balis, Ulysses G. J.; Camp, David G.; De, Asit K.; Harbrecht, Brian G.; Hayden, Douglas L.; Kaushal, Amit; O’Keefe, Grant E.; Kotz, Kenneth T.; Qian, Weijun; Schoenfeld, David A.; Shapiro, Michael B.; Silver, Geoffrey M.; Smith, Richard D.; Storey, John D.; Tibshirani, Robert; Toner, Mehmet; Wilhelmy, Julie; Wispelwey, Bram; Wong, Wing H

    2013-01-01

    A cornerstone of modern biomedical research is the use of mouse models to explore basic pathophysiological mechanisms, evaluate new therapeutic approaches, and make go or no-go decisions to carry new drug candidates forward into clinical trials. Systematic studies evaluating how well murine models mimic human inflammatory diseases are nonexistent. Here, we show that, although acute inflammatory stresses from different etiologies result in highly similar genomic responses in humans, the responses in corresponding mouse models correlate poorly with the human conditions and also, one another. Among genes changed significantly in humans, the murine orthologs are close to random in matching their human counterparts (e.g., R2 between 0.0 and 0.1). In addition to improvements in the current animal model systems, our study supports higher priority for translational medical research to focus on the more complex human conditions rather than relying on mouse models to study human inflammatory diseases. PMID:23401516

  10. A National Modeling Framework for Water Management Decisions

    Science.gov (United States)

    Bales, J. D.; Cline, D. W.; Pietrowsky, R.

    2013-12-01

    The National Weather Service (NWS), the U.S. Army Corps of Engineers (USACE), and the U.S. Geological Survey (USGS), all Federal agencies with complementary water-resources activities, entered into an Interagency Memorandum of Understanding (MOU) "Collaborative Science Services and Tools to Support Integrated and Adaptive Water Resources Management" to collaborate in activities that are supportive to their respective missions. One of the interagency activities is the development of a highly integrated national water modeling framework and information services framework. Together these frameworks establish a common operating picture, improve modeling and synthesis, support the sharing of data and products among agencies, and provide a platform for incorporation of new scientific understanding. Each of the agencies has existing operational systems to assist in carrying out their respective missions. The systems generally are designed, developed, tested, fielded, and supported by specialized teams. A broader, shared approach is envisioned and would include community modeling, wherein multiple independent investigators or teams develop and contribute new modeling capabilities based on science advances; modern technology in coupling model components and visualizing results; and a coupled atmospheric - hydrologic model construct such that the framework could be used in real-time water-resources decision making or for long-term management decisions. The framework also is being developed to account for organizational structures of the three partners such that, for example, national data sets can move down to the regional scale, and vice versa. We envision the national water modeling framework to be an important element of North American Water Program, to contribute to goals of the Program, and to be informed by the science and approaches developed as a part of the Program.

  11. Investment timing decisions in a stochastic duopoly model

    Energy Technology Data Exchange (ETDEWEB)

    Marseguerra, Giovanni [Istituto di Econometria e CRANEC, Universita Cattolica del Sacro Cuore di Milan (Italy)]. E-mail: giovanni.marseguerra@unicatt.it; Cortelezzi, Flavia [Dipartimento di Diritto ed Economia delle Persone e delle Imprese, Universita dell' Insubria (Italy)]. E-mail: flavia.cortelezzi@uninsubria.it; Dominioni, Armando [CORE-Catholique de Louvain la Neuve (Belgium)]. E-mail: dominioni@core.ucl.ac.be

    2006-08-15

    We investigate the role of strategic considerations on the optimal timing of investment when firms compete for a new market (e.g., the provision of an innovative product) under demand uncertainty. Within a continuous time model of stochastic oligopoly, we show that strategic considerations are likely to be of limited impact when the new product is radically innovative whilst the fear of a rival's entry may deeply affect firms' decisions whenever innovation is to some extent limited. The welfare analysis shows surprisingly that the desirability of the different market structures considered does not depend on the fixed entry cost.

  12. Markov Modeling with Soft Aggregation for Safety and Decision Analysis

    Energy Technology Data Exchange (ETDEWEB)

    COOPER,J. ARLIN

    1999-09-01

    The methodology in this report improves on some of the limitations of many conventional safety assessment and decision analysis methods. A top-down mathematical approach is developed for decomposing systems and for expressing imprecise individual metrics as possibilistic or fuzzy numbers. A ''Markov-like'' model is developed that facilitates combining (aggregating) inputs into overall metrics and decision aids, also portraying the inherent uncertainty. A major goal of Markov modeling is to help convey the top-down system perspective. One of the constituent methodologies allows metrics to be weighted according to significance of the attribute and aggregated nonlinearly as to contribution. This aggregation is performed using exponential combination of the metrics, since the accumulating effect of such factors responds less and less to additional factors. This is termed ''soft'' mathematical aggregation. Dependence among the contributing factors is accounted for by incorporating subjective metrics on ''overlap'' of the factors as well as by correspondingly reducing the overall contribution of these combinations to the overall aggregation. Decisions corresponding to the meaningfulness of the results are facilitated in several ways. First, the results are compared to a soft threshold provided by a sigmoid function. Second, information is provided on input ''Importance'' and ''Sensitivity,'' in order to know where to place emphasis on considering new controls that may be necessary. Third, trends in inputs and outputs are tracked in order to obtain significant information% including cyclic information for the decision process. A practical example from the air transportation industry is used to demonstrate application of the methodology. Illustrations are given for developing a structure (along with recommended inputs and weights) for air transportation oversight at three

  13. Model-Checking with Edge-Valued Decision Diagrams

    Science.gov (United States)

    Roux, Pierre; Siminiceanu, Radu I.

    2010-01-01

    We describe an algebra of Edge-Valued Decision Diagrams (EVMDDs) to encode arithmetic functions and its implementation in a model checking library along with state-of-the-art algorithms for building the transition relation and the state space of discrete state systems. We provide efficient algorithms for manipulating EVMDDs and give upper bounds of the theoretical time complexity of these algorithms for all basic arithmetic and relational operators. We also demonstrate that the time complexity of the generic recursive algorithm for applying a binary operator on EVMDDs is no worse than that of Multi-Terminal Decision Diagrams. We have implemented a new symbolic model checker with the intention to represent in one formalism the best techniques available at the moment across a spectrum of existing tools: EVMDDs for encoding arithmetic expressions, identity-reduced MDDs for representing the transition relation, and the saturation algorithm for reachability analysis. We compare our new symbolic model checking EVMDD library with the widely used CUDD package and show that, in many cases, our tool is several orders of magnitude faster than CUDD.

  14. Coupled hydrological, ecological, decision and economic models for monetary valuation of riparian ecosystem services

    Science.gov (United States)

    Goodrich, D. C.; Brookshire, D.; Broadbent, C.; Dixon, M. D.; Brand, L. A.; Thacher, J.; Benedict, K. K.; Lansey, K. E.; Stromberg, J. C.; Stewart, S.; McIntosh, M.

    2011-12-01

    Water is a critical component for sustaining both natural and human systems. Yet the value of water for sustaining ecosystem services is not well quantified in monetary terms. Ideally decisions involving water resource management would include an apples-to-apples comparison of the costs and benefits in dollars of both market and non-market goods and services - human and ecosystem. To quantify the value of non-market ecosystem services, scientifically defensible relationships must be developed that link the effect of a decision (e.g. human growth) to the change in ecosystem attributes from current conditions. It is this linkage that requires the "poly-disciplinary" coupling of knowledge and models from the behavioral, physical, and ecological sciences. In our experience another key component of making this successful linkage is development of a strong poly-disciplinary scientific team that can readily communicate complex disciplinary knowledge to non-specialists outside their own discipline. The time to build such a team that communicates well and has a strong sense of trust should not be underestimated. The research described in the presentation incorporated hydrologic, vegetation, avian, economic, and decision models into an integrated framework to determine the value of changes in ecological systems that result from changes in human water use. We developed a hydro-bio-economic framework for the San Pedro River Region in Arizona that considers groundwater, stream flow, and riparian vegetation, as well as abundance, diversity, and distribution of birds. In addition, we developed a similar framework for the Middle Rio Grande of New Mexico. There are six research components for this project: (1) decision support and scenario specification, (2) regional groundwater model, (3) the riparian vegetation model, (4) the avian model, (5) methods for displaying the information gradients in the valuation survey instruments (Choice Modeling and Contingent Valuation), and (6

  15. Decision model to control water losses in distribution networks

    Directory of Open Access Journals (Sweden)

    Marcele Elisa Fontana

    2016-01-01

    Full Text Available Abstract The losses in the urban water supply networks have become a growing concern. There are several alternatives for the quantification, detection and monitoring of water losses. However, in general, water companies have budgetary and other constraints that hinder implementation. Therefore, this paper presents a model to aid the selection of a subset of preventive maintenance actions to control water losses while accounting for the water companies’ restrictions. The model combines an additive multi-attribute value analysis by applying the SMARTER method to evaluate alternatives with Integer Linear Programming (ILP. The model shows to be efficient in order to achieve a portfolio of preventive maintenance actions, particularly when the decision maker considers that, there is a compensation for attribute evaluations.

  16. Neural correlates of forward planning in a spatial decision task in humans

    Science.gov (United States)

    Simon, Dylan Alexander; Daw, Nathaniel D.

    2011-01-01

    Although reinforcement learning (RL) theories have been influential in characterizing the brain’s mechanisms for reward-guided choice, the predominant temporal difference (TD) algorithm cannot explain many flexible or goal-directed actions that have been demonstrated behaviorally. We investigate such actions by contrasting an RL algorithm that is model-based, in that it relies on learning a map or model of the task and planning within it, to traditional model-free TD learning. To distinguish these approaches in humans, we used fMRI in a continuous spatial navigation task, in which frequent changes to the layout of the maze forced subjects continually to relearn their favored routes, thereby exposing the RL mechanisms employed. We sought evidence for the neural substrates of such mechanisms by comparing choice behavior and BOLD signals to decision variables extracted from simulations of either algorithm. Both choices and value-related BOLD signals in striatum, though most often associated with TD learning, were better explained by the model-based theory. Further, predecessor quantities for the model-based value computation were correlated with BOLD signals in the medial temporal lobe and frontal cortex. These results point to a significant extension of both the computational and anatomical substrates for RL in the brain. PMID:21471389

  17. Graph-based Models for Data and Decision Making

    Science.gov (United States)

    2016-02-16

    hulls. ACM 11un.saction.s on Mathematical Softwan, 22( 4):469-483, 1996. [2] M. Belkin and P. Niyogi. Laplacian eigenrnaps for dimensionality...cogntive models and user interfaces, and have explored relationships between mathematical and computational models of a detection task. Additionally... software have been developed for implementing these analyses and making them widely available. 15. SUBJECT TERMS Workload capacity modeling, human

  18. Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task

    Science.gov (United States)

    Moënne-Loccoz, Cristóbal; Vergara, Rodrigo C.; López, Vladimir; Mery, Domingo; Cosmelli, Diego

    2017-01-01

    Our daily interaction with the world is plagued of situations in which we develop expertise through self-motivated repetition of the same task. In many of these interactions, and especially when dealing with computer and machine interfaces, we must deal with sequences of decisions and actions. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion and a specific sequence of choices must be performed in order to produce the expected outcome. But, as we become experts in the use of such interfaces, is it possible to identify specific search and learning strategies? And if so, can we use this information to predict future actions? In addition to better understanding the cognitive processes underlying sequential decision making, this could allow building adaptive interfaces that can facilitate interaction at different moments of the learning curve. Here we tackle the question of modeling sequential decision-making behavior in a simple human-computer interface that instantiates a 4-level binary decision tree (BDT) task. We record behavioral data from voluntary participants while they attempt to solve the task. Using a Hidden Markov Model-based approach that capitalizes on the hierarchical structure of behavior, we then model their performance during the interaction. Our results show that partitioning the problem space into a small set of hierarchically related stereotyped strategies can potentially capture a host of individual decision making policies. This allows us to follow how participants learn and develop expertise in the use of the interface. Moreover, using a Mixture of Experts based on these stereotyped strategies, the model is able to predict the behavior of participants that master the task. PMID:28943847

  19. Temporal characteristics of the influence of punishment on perceptual decision making in the human brain

    OpenAIRE

    Blank, H.; Guido, B.; Heekeren, H.R.; Philiastides, M.G.

    2013-01-01

    Perceptual decision making is the process by which information from sensory systems is combined and used to influence our behavior. In addition to the sensory input, this process can be affected by other factors, such as reward and punishment for correct and incorrect responses. To investigate the temporal dynamics of how monetary punishment influences perceptual decision making in humans, we collected electroencephalography (EEG) data during a perceptual categorization task whereby the punis...

  20. Modeling violations of the race model inequality in bimodal paradigms: co-activation from decision and non-decision components

    Directory of Open Access Journals (Sweden)

    Michael eZehetleitner

    2015-03-01

    Full Text Available The redundant-signals paradigm (RSP is designed to investigate response behavior in perceptual tasks in which response-relevant targets are defined by either one or two features, or modalities. The common finding is that responses are speeded for redundantly compared to singly defined targets. This redundant-signals effect (RSE can be accounted for by race models if the response times do not violate the race model inequality (RMI. When there are violations of the RMI, race models are effectively excluded as a viable account of the RSE. The common alternative is provided by co-activation accounts, which assume that redundant target signals are integrated at some processing stage. However, ‘co-activation’ has mostly been only indirectly inferred and the accounts have only rarely been explicitly modeled; if they were modeled, the RSE has typically been assumed to have a decisional locus. Yet, there are also indications in the literature that the RSE might originate, at least in part, at a non-decisional or motor stage. In the present study, using a distribution analysis of sequential-sampling models (ex-Wald and Ratcliff Diffusion model, the locus of the RSE was investigated for two bimodal (audio-visual detection tasks that strongly violated the RMI, indicative of substantial co-activation. Three model variants assuming different loci of the RSE were fitted to the quantile reaction time proportions: a decision, a non-decision, and a combined variant both to vincentized group as well as individual data. The results suggest that for the two bimodal detection tasks, co-activation has a shared decisional and non-decisional locus. These findings point to the possibility that the mechanisms underlying the RSE depend on the specifics (task, stimulus, conditions, etc. of the experimental paradigm.

  1. Modeling violations of the race model inequality in bimodal paradigms: co-activation from decision and non-decision components.

    Science.gov (United States)

    Zehetleitner, Michael; Ratko-Dehnert, Emil; Müller, Hermann J

    2015-01-01

    The redundant-signals paradigm (RSP) is designed to investigate response behavior in perceptual tasks in which response-relevant targets are defined by either one or two features, or modalities. The common finding is that responses are speeded for redundantly compared to singly defined targets. This redundant-signals effect (RSE) can be accounted for by race models if the response times do not violate the race model inequality (RMI). When there are violations of the RMI, race models are effectively excluded as a viable account of the RSE. The common alternative is provided by co-activation accounts, which assume that redundant target signals are integrated at some processing stage. However, "co-activation" has mostly been only indirectly inferred and the accounts have only rarely been explicitly modeled; if they were modeled, the RSE has typically been assumed to have a decisional locus. Yet, there are also indications in the literature that the RSE might originate, at least in part, at a non-decisional or motor stage. In the present study, using a distribution analysis of sequential-sampling models (ex-Wald and Ratcliff Diffusion model), the locus of the RSE was investigated for two bimodal (audio-visual) detection tasks that strongly violated the RMI, indicative of substantial co-activation. Three model variants assuming different loci of the RSE were fitted to the quantile reaction time proportions: a decision, a non-decision, and a combined variant both to vincentized group as well as individual data. The results suggest that for the two bimodal detection tasks, co-activation has a shared decisional and non-decisional locus. These findings point to the possibility that the mechanisms underlying the RSE depend on the specifics (task, stimulus, conditions, etc.) of the experimental paradigm.

  2. Multicriteria decision group model for the selection of suppliers

    Directory of Open Access Journals (Sweden)

    Luciana Hazin Alencar

    2008-08-01

    Full Text Available Several authors have been studying group decision making over the years, which indicates how relevant it is. This paper presents a multicriteria group decision model based on ELECTRE IV and VIP Analysis methods, to those cases where there is great divergence among the decision makers. This model includes two stages. In the first, the ELECTRE IV method is applied and a collective criteria ranking is obtained. In the second, using criteria ranking, VIP Analysis is applied and the alternatives are selected. To illustrate the model, a numerical application in the context of the selection of suppliers in project management is used. The suppliers that form part of the project team have a crucial role in project management. They are involved in a network of connected activities that can jeopardize the success of the project, if they are not undertaken in an appropriate way. The question tackled is how to select service suppliers for a project on behalf of an enterprise that assists the multiple objectives of the decision-makers.Vários autores têm estudado decisão em grupo nos últimos anos, o que indica a relevância do assunto. Esse artigo apresenta um modelo multicritério de decisão em grupo baseado nos métodos ELECTRE IV e VIP Analysis, adequado aos casos em que se tem uma grande divergência entre os decisores. Esse modelo é composto por dois estágios. No primeiro, o método ELECTRE IV é aplicado e uma ordenação dos critérios é obtida. No próximo estágio, com a ordenação dos critérios, o método VIP Analysis é aplicado e as alternativas são selecionadas. Para ilustrar o modelo, uma aplicação numérica no contexto da seleção de fornecedores em projetos é realizada. Os fornecedores que fazem parte da equipe do projeto têm um papel fundamental no gerenciamento de projetos. Eles estão envolvidos em uma rede de atividades conectadas que, caso não sejam executadas de forma apropriada, podem colocar em risco o sucesso do

  3. A generic concept for the development of model-guided clinical decision support systems

    Directory of Open Access Journals (Sweden)

    Denecke Kerstin

    2015-09-01

    Full Text Available Disease development and progression are very complex processes which make clinical decision making non-trivial. On the one hand, examination results that are stored in multiple formats and data types in clinical information systems need to be considered. Beyond, biological or molecular-biological processes can influence clinical decision making. So far, biological knowledge and patient data is separated from each other. This complicates inclusion of all relevant knowledge and information into the decision making. In this paper, we describe a concept of model-based decision support that links knowledge about biological processes, treatment decisions and clinical data. It consists of three models: 1 a biological model, 2 a decision model encompassing medical knowledge about the treatment workflow and decision parameters, and 3 a patient data model generated from clinical data. Requirements and future steps for realizing the concept will be presented and it will be shown how the concept can support the clinical decision making.

  4. Work-life Balance Decision-making of Norwegian Students: Implications for Human Resources Management

    Directory of Open Access Journals (Sweden)

    Remigiusz Gawlik

    2016-12-01

    Full Text Available Objective: The paper aims at identifying and assessing the significance of work-life balance determinants between the Youth of highly developed societies and its implications for human resources management on the example of Norway. Research Design & Methods: The research target group consists of 236 respondents recruited among Norwegian tertiary education students. It employed literature analysis, two-stage exploratory research: direct individual in-depth interviews, survey based on a self-administered, web-based questionnaire with single-answer, limited choice qualitative & quantitative, as well as explanatory research (informal moderated group discussions. Findings: The research on perceptions of determinants of quality of life and attractiveness of life strategies shows that in a country with relatively high socio-economic development level, such as Norway, differences in rankings do exist. They can be observed in relevance to both material and non-material QoL determinants. Implications & Recommendations: The study revealed a need for deeper research on individually driven early decision-making of future employees and entrepreneurs. This will result in closer modelling of socio-economic phenomena, including more accurate adaptation to trends on the labour market and creation of new business models. Contribution & Value Added: Research value added comes from the comparison of perceptions of quality of life determinants between countries at various stages of socio-economic development and its implications for human resource management.

  5. An Evaluation of the Decision-Making Capacity Assessment Model

    Science.gov (United States)

    Brémault-Phillips, Suzette C.; Parmar, Jasneet; Friesen, Steven; Rogers, Laura G.; Pike, Ashley; Sluggett, Bryan

    2016-01-01

    Background The Decision-Making Capacity Assessment (DMCA) Model includes a best-practice process and tools to assess DMCA, and implementation strategies at the organizational and assessor levels to support provision of DMCAs across the care continuum. A Developmental Evaluation of the DMCA Model was conducted. Methods A mixed methods approach was used. Survey (N = 126) and focus group (N = 49) data were collected from practitioners utilizing the Model. Results Strengths of the Model include its best-practice and implementation approach, applicability to independent practitioners and inter-professional teams, focus on training/mentoring to enhance knowledge/skills, and provision of tools/processes. Post-training, participants agreed that they followed the Model’s guiding principles (90%), used problem-solving (92%), understood discipline-specific roles (87%), were confident in their knowledge of DMCAs (75%) and pertinent legislation (72%), accessed consultative services (88%), and received management support (64%). Model implementation is impeded when role clarity, physician engagement, inter-professional buy-in, accountability, dedicated resources, information sharing systems, and remuneration are lacking. Dedicated resources, job descriptions inclusive of DMCAs, ongoing education/mentoring supports, access to consultative services, and appropriate remuneration would support implementation. Conclusions The DMCA Model offers practitioners, inter-professional teams, and organizations a best-practice and implementation approach to DMCAs. Addressing barriers and further contextualizing the Model would be warranted. PMID:27729947

  6. Implementation of Dynamic Smart Decision Model for Vertical Handoff

    Science.gov (United States)

    Sahni, Nidhi

    2010-11-01

    International Mobile Telecommunications-Advanced (IMT Advanced), better known as 4G is the next level of evolution in the field of wireless communications. 4G Wireless networks enable users to access information anywhere, anytime, with a seamless connection to a wide range of information and services, and receiving a large volume of information, data, pictures, video and thus increasing the demand for High Bandwidth and Signal Strength. The mobility among various networks is achieved through Vertical Handoff. Vertical handoffs refer to the automatic failover from one technology to another in order to maintain communication. The heterogeneous co-existence of access technologies with largely different characteristics creates a decision problem of determining the "best" available network at "best" time for handoff. In this paper, we implemented the proposed Dynamic and Smart Decision model to decide the "best" network interface and "best" time moment to handoff. The proposed model implementation not only demonstrates the individual user needs but also improve the whole system performance i.e. Quality of Service by reducing the unnecessary handoffs and maintain mobility.

  7. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    Science.gov (United States)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  8. A queueing model of pilot decision making in a multi-task flight management situation

    Science.gov (United States)

    Walden, R. S.; Rouse, W. B.

    1977-01-01

    Allocation of decision making responsibility between pilot and computer is considered and a flight management task, designed for the study of pilot-computer interaction, is discussed. A queueing theory model of pilot decision making in this multi-task, control and monitoring situation is presented. An experimental investigation of pilot decision making and the resulting model parameters are discussed.

  9. A Composite Modelling Approach to Decision Support by the Use of the CBA-DK Model

    DEFF Research Database (Denmark)

    Barfod, Michael Bruhn; Salling, Kim Bang; Leleur, Steen

    2007-01-01

    This paper presents a decision support system for assessment of transport infrastructure projects. The composite modelling approach, COSIMA, combines a cost-benefit analysis by use of the CBA-DK model with multi-criteria analysis applying the AHP and SMARTER techniques. The modelling uncertainties...

  10. Prediction model based on decision tree analysis for laccase mediators.

    Science.gov (United States)

    Medina, Fabiola; Aguila, Sergio; Baratto, Maria Camilla; Martorana, Andrea; Basosi, Riccardo; Alderete, Joel B; Vazquez-Duhalt, Rafael

    2013-01-10

    A Structure Activity Relationship (SAR) study for laccase mediator systems was performed in order to correctly classify different natural phenolic mediators. Decision tree (DT) classification models with a set of five quantum-chemical calculated molecular descriptors were used. These descriptors included redox potential (ɛ°), ionization energy (E(i)), pK(a), enthalpy of formation of radical (Δ(f)H), and OH bond dissociation energy (D(O-H)). The rationale for selecting these descriptors is derived from the laccase-mediator mechanism. To validate the DT predictions, the kinetic constants of different compounds as laccase substrates, their ability for pesticide transformation as laccase-mediators, and radical stability were experimentally determined using Coriolopsis gallica laccase and the pesticide dichlorophen. The prediction capability of the DT model based on three proposed descriptors showed a complete agreement with the obtained experimental results. Copyright © 2012 Elsevier Inc. All rights reserved.

  11. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    Directory of Open Access Journals (Sweden)

    Chung-Min Wu

    2013-01-01

    Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

  12. Diffusion Based Modeling of Human Brain Response to External Stimuli

    CERN Document Server

    Namazi, Hamidreza

    2012-01-01

    Human brain response is the overall ability of the brain in analyzing internal and external stimuli in the form of transferred energy to the mind/brain phase-space and thus, making the proper decisions. During the last decade scientists discovered about this phenomenon and proposed some models based on computational, biological, or neuropsychological methods. Despite some advances in studies related to this area of the brain research there was less effort which have been done on the mathematical modeling of the human brain response to external stimuli. This research is devoted to the modeling of human EEG signal, as an alert state of overall human brain activity monitoring, due to receiving external stimuli, based on fractional diffusion equation. The results of this modeling show very good agreement with the real human EEG signal and thus, this model can be used as a strong representative of the human brain activity.

  13. Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

    Science.gov (United States)

    Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

    2015-01-01

    Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector

  14. Decoding Problem Gamblers' Signals: A Decision Model for Casino Enterprises.

    Science.gov (United States)

    Ifrim, Sandra

    2015-12-01

    The aim of the present study is to offer a validated decision model for casino enterprises. The model enables those users to perform early detection of problem gamblers and fulfill their ethical duty of social cost minimization. To this end, the interpretation of casino customers' nonverbal communication is understood as a signal-processing problem. Indicators of problem gambling recommended by Delfabbro et al. (Identifying problem gamblers in gambling venues: final report, 2007) are combined with Viterbi algorithm into an interdisciplinary model that helps decoding signals emitted by casino customers. Model output consists of a historical path of mental states and cumulated social costs associated with a particular client. Groups of problem and non-problem gamblers were simulated to investigate the model's diagnostic capability and its cost minimization ability. Each group consisted of 26 subjects and was subsequently enlarged to 100 subjects. In approximately 95% of the cases, mental states were correctly decoded for problem gamblers. Statistical analysis using planned contrasts revealed that the model is relatively robust to the suppression of signals performed by casino clientele facing gambling problems as well as to misjudgments made by staff regarding the clients' mental states. Only if the last mentioned source of error occurs in a very pronounced manner, i.e. judgment is extremely faulty, cumulated social costs might be distorted.

  15. Influence of Biases in Numerical Magnitude allocation on Human Pro-Social Decision Making.

    Science.gov (United States)

    Arshad, Qadeer; Nigmatullina, Yuliya; Siddiqui, Shuaib; Franka, Mustafa; Mediratta, Saniya; Ramachandaran, Sanjeev; Lobo, Rhannon; Malhotra, Paresh; Roberts, R Edward; Bronstein, Adolfo M

    2017-09-13

    Over the past decade neuroscientific research has attempted to probe the neurobiological underpinnings of human pro-social decision-making. Such research has almost ubiquitously employed tasks such as the dictator game or similar variations (i.e. ultimatum game). Considering the explicit numerical nature of such tasks, it is surprising that the influence of numerical cognition upon decision-making during task performance remains unknown. Whilst performing these tasks, participants typically tend to anchor upon a 50:50 split that necessitates an explicit numerical judgement (i.e. number-pair bisection). Accordingly, we hypothesise that the decision-making process during the dictator game recruits overlapping cognitive processes to those known to be engaged during number-pair bisection. We observed that biases in numerical magnitude allocation correlated with the formulation of decisions during the dictator game. That is, intrinsic biases towards smaller numerical magnitudes were associated with the formulation of less favourable decisions, whereas biases towards larger magnitudes were associated with more favourable choices. We proceeded to corroborate this relationship by subliminally and systematically inducing biases in numerical magnitude towards either higher or lower numbers using a visuo-vestibular stimulation paradigm. Such subliminal alterations in numerical magnitude allocation led to proportional and corresponding changes to an individual's decision-making during the dictator game. Critically, no relationship was observed between neither intrinsic nor induced biases in numerical magnitude on decision-making when assessed using a non-numerical based pro-social questionnaire. Our findings demonstrate numerical influences upon decisions formulated during the dictator game and highlight the necessity to control for confounds associated with numerical cognition in human decision-making paradigms. Copyright © 2017, Journal of Neurophysiology.

  16. Detection of Unusual Human Activities Based on Behavior Modeling

    OpenAIRE

    Hiraishi, Kunihiko; Kobayashi, Koichi

    2014-01-01

    A type of services that require human physical actions and intelligent decision making exists in various real fields, such as nursing in hospitals and caregiving in nursing homes. In this paper, we propose new formalism for modeling human behavior in such services. Behavior models are estimated from event-logs, and can be used for analysis of human activities. We show two analysis methods: one is to detect unusual human activities that appear in event-logs, and the other is to find staffs tha...

  17. Examining the Resilience of Crop Production, Livestock Carrying Capacity, and Woodland Density in a Rural Zimbabwean Socio-Ecological System Using Agent-Based Models Representing Human Management Decisions

    Science.gov (United States)

    Eitzel Solera, M. V.; Neves, K.; Veski, A.; Solera, J.; Omoju, O. E.; Mawere Ndlovu, A.; Wilson, K.

    2016-12-01

    As climate change increases the pressures on arid ecosystems by changing timing and amount of rainfall, understanding the ways in which human management choices affect the resilience of these systems becomes key to their sustainability. On marginal farmland in Mazvihwa, Midlands Province, the historical carrying capacity of livestock has been consistently surprisingly high. We explore this phenomenon by building an agent-based model in NetLogo from a wealth of long-term data generated by the community-based participatory research team of The Muonde Trust, a Zimbabwean non-governmental organization. We combine the accumulated results of 35 years of indigenous and local knowledge with national datasets such as rainfall records. What factors keep the carrying capacity high? What management choices can maintain crops, livestock, and woodland at levels necessary for the community's survival? How do these choices affect long-term sustainability, and does increasing resilience at one scale reduce resilience at another scale? We use our agent-based model to explore the feedbacks between crops, livestock, and woodland and the impacts of various human choices as well as temporal and spatial ecological variation. By testing different scenarios, we disentangle the complex interactions between these components. We find that some factors out of the community's control can strongly affect the sustainability of the system through times of drought, and that supplementary feed may maintain livestock potentially at the expense of other resources. The challenges to resilience encountered by the farmers in Mazvihwa are not unique - many indigenous and rural people face drought and the legacies of colonialism, which contribute to lowered resilience to external challenges such as climate change, epidemics, and political instability. Using the agent-based model as a tool for synthesis and exploration initiates discussion about resilience-enhancing management choices for Mazvihwa's farmer-researchers.

  18. Standardizing Benchmark Dose Calculations to Improve Science-Based Decisions in Human Health Assessments

    Science.gov (United States)

    Wignall, Jessica A.; Shapiro, Andrew J.; Wright, Fred A.; Woodruff, Tracey J.; Chiu, Weihsueh A.; Guyton, Kathryn Z.

    2014-01-01

    Background: Benchmark dose (BMD) modeling computes the dose associated with a prespecified response level. While offering advantages over traditional points of departure (PODs), such as no-observed-adverse-effect-levels (NOAELs), BMD methods have lacked consistency and transparency in application, interpretation, and reporting in human health assessments of chemicals. Objectives: We aimed to apply a standardized process for conducting BMD modeling to reduce inconsistencies in model fitting and selection. Methods: We evaluated 880 dose–response data sets for 352 environmental chemicals with existing human health assessments. We calculated benchmark doses and their lower limits [10% extra risk, or change in the mean equal to 1 SD (BMD/L10/1SD)] for each chemical in a standardized way with prespecified criteria for model fit acceptance. We identified study design features associated with acceptable model fits. Results: We derived values for 255 (72%) of the chemicals. Batch-calculated BMD/L10/1SD values were significantly and highly correlated (R2 of 0.95 and 0.83, respectively, n = 42) with PODs previously used in human health assessments, with values similar to reported NOAELs. Specifically, the median ratio of BMDs10/1SD:NOAELs was 1.96, and the median ratio of BMDLs10/1SD:NOAELs was 0.89. We also observed a significant trend of increasing model viability with increasing number of dose groups. Conclusions: BMD/L10/1SD values can be calculated in a standardized way for use in health assessments on a large number of chemicals and critical effects. This facilitates the exploration of health effects across multiple studies of a given chemical or, when chemicals need to be compared, providing greater transparency and efficiency than current approaches. Citation: Wignall JA, Shapiro AJ, Wright FA, Woodruff TJ, Chiu WA, Guyton KZ, Rusyn I. 2014. Standardizing benchmark dose calculations to improve science-based decisions in human health assessments. Environ Health

  19. Combined Economic and Hydrologic Modeling to Support Collaborative Decision Making Processes

    Science.gov (United States)

    Sheer, D. P.

    2008-12-01

    For more than a decade, the core concept of the author's efforts in support of collaborative decision making has been a combination of hydrologic simulation and multi-objective optimization. The modeling has generally been used to support collaborative decision making processes. The OASIS model developed by HydroLogics Inc. solves a multi-objective optimization at each time step using a mixed integer linear program (MILP). The MILP can be configured to include any user defined objective, including but not limited too economic objectives. For example, an estimated marginal value for water for crops and M&I use were included in the objective function to drive trades in a model of the lower Rio Grande. The formulation of the MILP, constraints and objectives, in any time step is conditional: it changes based on the value of state variables and dynamic external forcing functions, such as rainfall, hydrology, market prices, arrival of migratory fish, water temperature, etc. It therefore acts as a dynamic short term multi-objective economic optimization for each time step. MILP is capable of solving a general problem that includes a very realistic representation of the physical system characteristics in addition to the normal multi-objective optimization objectives and constraints included in economic models. In all of these models, the short term objective function is a surrogate for achieving long term multi-objective results. The long term performance for any alternative (especially including operating strategies) is evaluated by simulation. An operating rule is the combination of conditions, parameters, constraints and objectives used to determine the formulation of the short term optimization in each time step. Heuristic wrappers for the simulation program have been developed improve the parameters of an operating rule, and are initiating research on a wrapper that will allow us to employ a genetic algorithm to improve the form of the rule (conditions, constraints

  20. Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats.

    Directory of Open Access Journals (Sweden)

    Claire A Hales

    Full Text Available Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142, and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward.

  1. Diffusion Modelling Reveals the Decision Making Processes Underlying Negative Judgement Bias in Rats.

    Science.gov (United States)

    Hales, Claire A; Robinson, Emma S J; Houghton, Conor J

    2016-01-01

    Human decision making is modified by emotional state. Rodents exhibit similar biases during interpretation of ambiguous cues that can be altered by affective state manipulations. In this study, the impact of negative affective state on judgement bias in rats was measured using an ambiguous-cue interpretation task. Acute treatment with an anxiogenic drug (FG7142), and chronic restraint stress and social isolation both induced a bias towards more negative interpretation of the ambiguous cue. The diffusion model was fit to behavioural data to allow further analysis of the underlying decision making processes. To uncover the way in which parameters vary together in relation to affective state manipulations, independent component analysis was conducted on rate of information accumulation and distances to decision threshold parameters for control data. Results from this analysis were applied to parameters from negative affective state manipulations. These projected components were compared to control components to reveal the changes in decision making processes that are due to affective state manipulations. Negative affective bias in rodents induced by either FG7142 or chronic stress is due to a combination of more negative interpretation of the ambiguous cue, reduced anticipation of the high reward and increased anticipation of the low reward.

  2. Qualitative modeling of the decision-making process using electrooculography.

    Science.gov (United States)

    Marandi, Ramtin Zargari; Sabzpoushan, S H

    2015-12-01

    A novel method based on electrooculography (EOG) has been introduced in this work to study the decision-making process. An experiment was designed and implemented wherein subjects were asked to choose between two items from the same category that were presented within a limited time. The EOG and voice signals of the subjects were recorded during the experiment. A calibration task was performed to map the EOG signals to their corresponding gaze positions on the screen by using an artificial neural network. To analyze the data, 16 parameters were extracted from the response time and EOG signals of the subjects. Evaluation and comparison of the parameters, together with subjects' choices, revealed functional information. On the basis of this information, subjects switched their eye gazes between items about three times on average. We also found, according to statistical hypothesis testing-that is, a t test, t(10) = 71.62, SE = 1.25, p < .0001-that the correspondence rate of a subjects' gaze at the moment of selection with the selected item was significant. Ultimately, on the basis of these results, we propose a qualitative choice model for the decision-making task.

  3. Perceptual decision making: Drift-diffusion model is equivalent to a Bayesian model

    Directory of Open Access Journals (Sweden)

    Sebastian eBitzer

    2014-02-01

    Full Text Available Behavioural data obtained with perceptual decision making experiments are typically analysed with the drift-diffusion model. This parsimonious model accumulates noisy pieces of evidence towards a decision bound to explain the accuracy and reaction times of subjects. Recently, Bayesian models have been proposed to explain how the brain extracts information from noisy input as typically presented in perceptual decision making tasks. It has long been known that the drift-diffusion model is tightly linked with such functional Bayesian models but the precise relationship of the two mechanisms was never made explicit. Using a Bayesian model, we derived the equations which relate parameter values between these models. In practice we show that this equivalence is useful when fitting multi-subject data. We further show that the Bayesian model suggests different decision variables which all predict equal responses and discuss how these may be discriminated based on neural correlates of accumulated evidence. In addition, we discuss extensions to the Bayesian model which would be difficult to derive for the drift-diffusion model. We suggest that these and other extensions may be highly useful for deriving new experiments which test novel hypotheses.

  4. Human decision making based on variations in internal noise: an EEG study.

    Directory of Open Access Journals (Sweden)

    Sygal Amitay

    Full Text Available Perceptual decision making is prone to errors, especially near threshold. Physiological, behavioural and modeling studies suggest this is due to the intrinsic or 'internal' noise in neural systems, which derives from a mixture of bottom-up and top-down sources. We show here that internal noise can form the basis of perceptual decision making when the external signal lacks the required information for the decision. We recorded electroencephalographic (EEG activity in listeners attempting to discriminate between identical tones. Since the acoustic signal was constant, bottom-up and top-down influences were under experimental control. We found that early cortical responses to the identical stimuli varied in global field power and topography according to the perceptual decision made, and activity preceding stimulus presentation could predict both later activity and behavioural decision. Our results suggest that activity variations induced by internal noise of both sensory and cognitive origin are sufficient to drive discrimination judgments.

  5. Introducing Complex Decision Models to the Decision Maker with Computer Software - The Profile Distance Method (PDM

    Directory of Open Access Journals (Sweden)

    Edward Bernroider

    2010-06-01

    Full Text Available In this paper we demonstrate how the profile distance method was transformed into a software environment enabling the decision maker to utilize a complex decision making tool without any advanced knowledge of the underlying mathematical and technical features. We present theoretical and technical aspects as well as contextual and usage related information from the viewpoint of the decision maker. Preliminary empirical results suggest that the developed software component is effective in terms of platform independence, usability and intuitive interface design. The data showed a good rating for usefulness, which, however, was targeted as the main goal for further development.

  6. A classification of the multiple criteria decision making models

    OpenAIRE

    Guerras Martín, Luis Angel

    1987-01-01

    In this work we have tried to present a classification of multiobjective techniques based in the relationship between the main subJects of decision process: analyst and decision maker. These relation, in terms of information flows, have important consequences for decision making processes in business organizations.

  7. Fuzzy Multiple Criteria Decision Making Model with Fuzzy Time Weight Scheme

    Directory of Open Access Journals (Sweden)

    Chin-Yao Low

    2013-11-01

    Full Text Available In this study, we purpose a common fuzzy multiple criteria decision making model. A brand new concept - fuzzy time weighted scheme is adopted for considering in the model to establish a fuzzy multiple criteria decision making with time weight (FMCDMTW model. A real case of fuzzy multiple criteria decision making (FMCDM problems to be considering in this study. The performance evaluation of auction websites based on all criteria proposed in related literature. Obviously, the problem under investigated is a FMCDM problem with historic data and recent data. Since the evaluated criteria proposed in the literature cannot be defined precisely and numerically, fuzzy linguistic terms can be used to aggregate them numerically.  It not only conforms to human cognition but also benefits interpretation. Furthermore, notice that the literature considered contains certain amount of historic data. Equally weighted historic data is usually considered in FMCDM problems, and this approach would introduce bias owing to the collected data for a certain long time period.  As a result, fuzzy time weighted technique is adopted to resolve this issue.  

  8. The Nature of Belief-Directed Exploratory Choice in Human Decision-Making

    Directory of Open Access Journals (Sweden)

    W. Bradley Knox

    2012-01-01

    Full Text Available In non-stationary environments, there is a conflict between exploiting currently favored options and gaining information by exploring lesser-known options that in the past have proven less rewarding. Optimal decision making in such tasks requires considering future states of the environment (i.e., planning and properly updating beliefs about the state of environment after observing outcomes associated with choices. Optimal belief-updating is reflective in that beliefs can change without directly observing environmental change. For example, after ten seconds elapse, one might correctly believe that a traffic light last observed to be red is now more likely to be green. To understand human decision-making when rewards associated with choice options change over time, we develop a variant of the classic bandit task that is both rich enough to encompass relevant phenomena and sufficiently tractable to allow for ideal actor analysis of sequential choice behavior. We evaluate whether people update beliefs about the state of environment in a reflexive (i.e., only in response to observed changes in reward structure or reflective manner. In contrast to purely "random" accounts of exploratory behavior, model-based analyses of the subjects’ choices and latencies indicate that people are reflective belief-updaters. However, unlike the Ideal Actor model, our analyses indicate that people's choice behavior does not reflect consideration of future environmental states. Thus, although people update beliefs in a reflective manner consistent with the ideal actor, they do not engage in optimal long-term planning, but instead myopically choose the option on every trial that is believed to have the highest immediate payoff.

  9. Mathematical models of human behavior

    DEFF Research Database (Denmark)

    Møllgaard, Anders Edsberg

    data set, along with work on other behavioral data. The overall goal is to contribute to a quantitative understanding of human behavior using big data and mathematical models. Central to the thesis is the determination of the predictability of different human activities. Upper limits are derived......, thereby implying that interactions between spreading processes are driving forces of attention dynamics. Overall, the thesis contributes to a quantitative understanding of a wide range of different human behaviors by applying mathematical modeling to behavioral data. There can be no doubt......During the last 15 years there has been an explosion in human behavioral data caused by the emergence of cheap electronics and online platforms. This has spawned a whole new research field called computational social science, which has a quantitative approach to the study of human behavior. Most...

  10. Personal experience and reputation interact in human decisions to help reciprocally.

    Science.gov (United States)

    Molleman, Lucas; van den Broek, Eva; Egas, Martijn

    2013-04-22

    There is ample evidence that human cooperative behaviour towards other individuals is often conditioned on information about previous interactions. This information derives both from personal experience (direct reciprocity) and from experience of others (i.e. reputation; indirect reciprocity). Direct and indirect reciprocity have been studied separately, but humans often have access to both types of information. Here, we experimentally investigate information use in a repeated helping game. When acting as donor, subjects can condition their decisions to help recipients with both types of information at a small cost to access such information. We find that information from direct interactions weighs more heavily in decisions to help, and participants tend to react less forgivingly to negative personal experience than to negative reputation. Moreover, effects of personal experience and reputation interact in decisions to help. If a recipient's reputation is positive, the personal experience of the donor has a weak effect on the decision to help, and vice versa. Yet if the two types of information indicate conflicting signatures of helpfulness, most decisions to help follow personal experience. To understand the roles of direct and indirect reciprocity in human cooperation, they should be studied in concert, not in isolation.

  11. Conflicting Ideologies: Simulating Significant Historical Human Decision Processes.

    Science.gov (United States)

    Gerson, Charles W.

    1998-01-01

    A formative small-group (n12) evaluation of a pair of opposed computer simulations modeling the thinking of historical ideologies (communist insurgency and counter-insurgency) suggests simulations had value in stimulating and modifying assessments of roles within real-world settings. Explores basic objective of having the simulation user develop a…

  12. Impact of modellers' decisions on hydrological a priori predictions

    Science.gov (United States)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2014-06-01

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

  13. Maintenance modeling and optimization integrating human and material resources

    Energy Technology Data Exchange (ETDEWEB)

    Martorell, S., E-mail: smartore@iqn.upv.e [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Villamizar, M.; Carlos, S. [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Sanchez, A. [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia (Spain)

    2010-12-15

    Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.

  14. Selection of Representative Models for Decision Analysis Under Uncertainty

    Science.gov (United States)

    Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.

    2016-03-01

    The decision-making process in oil fields includes a step of risk analysis associated with the uncertainties present in the variables of the problem. Such uncertainties lead to hundreds, even thousands, of possible scenarios that are supposed to be analyzed so an effective production strategy can be selected. Given this high number of scenarios, a technique to reduce this set to a smaller, feasible subset of representative scenarios is imperative. The selected scenarios must be representative of the original set and also free of optimistic and pessimistic bias. This paper is devoted to propose an assisted methodology to identify representative models in oil fields. To do so, first a mathematical function was developed to model the representativeness of a subset of models with respect to the full set that characterizes the problem. Then, an optimization tool was implemented to identify the representative models of any problem, considering not only the cross-plots of the main output variables, but also the risk curves and the probability distribution of the attribute-levels of the problem. The proposed technique was applied to two benchmark cases and the results, evaluated by experts in the field, indicate that the obtained solutions are richer than those identified by previously adopted manual approaches. The program bytecode is available under request.

  15. Agricultural Model for the Nile Basin Decision Support System

    Science.gov (United States)

    van der Bolt, Frank; Seid, Abdulkarim

    2014-05-01

    To analyze options for increasing food supply in the Nile basin the Nile Agricultural Model (AM) was developed. The AM includes state-of-the-art descriptions of biophysical, hydrological and economic processes and realizes a coherent and consistent integration of hydrology, agronomy and economics. The AM covers both the agro-ecological domain (water, crop productivity) and the economic domain (food supply, demand, and trade) and allows to evaluate the macro-economic and hydrological impacts of scenarios for agricultural development. Starting with the hydrological information from the NileBasin-DSS the AM calculates the available water for agriculture, the crop production and irrigation requirements with the FAO-model AquaCrop. With the global commodity trade model MAGNET scenarios for land development and conversion are evaluated. The AM predicts consequences for trade, food security and development based on soil and water availability, crop allocation, food demand and food policy. The model will be used as a decision support tool to contribute to more productive and sustainable agriculture in individual Nile countries and the whole region.

  16. Agricultural climate impacts assessment for economic modeling and decision support

    Science.gov (United States)

    Thomson, A. M.; Izaurralde, R. C.; Beach, R.; Zhang, X.; Zhao, K.; Monier, E.

    2013-12-01

    A range of approaches can be used in the application of climate change projections to agricultural impacts assessment. Climate projections can be used directly to drive crop models, which in turn can be used to provide inputs for agricultural economic or integrated assessment models. These model applications, and the transfer of information between models, must be guided by the state of the science. But the methodology must also account for the specific needs of stakeholders and the intended use of model results beyond pure scientific inquiry, including meeting the requirements of agencies responsible for designing and assessing policies, programs, and regulations. Here we present methodology and results of two climate impacts studies that applied climate model projections from CMIP3 and from the EPA Climate Impacts and Risk Analysis (CIRA) project in a crop model (EPIC - Environmental Policy Indicator Climate) in order to generate estimates of changes in crop productivity for use in an agricultural economic model for the United States (FASOM - Forest and Agricultural Sector Optimization Model). The FASOM model is a forward-looking dynamic model of the US forest and agricultural sector used to assess market responses to changing productivity of alternative land uses. The first study, focused on climate change impacts on the UDSA crop insurance program, was designed to use available daily climate projections from the CMIP3 archive. The decision to focus on daily data for this application limited the climate model and time period selection significantly; however for the intended purpose of assessing impacts on crop insurance payments, consideration of extreme event frequency was critical for assessing periodic crop failures. In a second, coordinated impacts study designed to assess the relative difference in climate impacts under a no-mitigation policy and different future climate mitigation scenarios, the stakeholder specifically requested an assessment of a

  17. A Markov decision model for determining optimal outpatient scheduling.

    Science.gov (United States)

    Patrick, Jonathan

    2012-06-01

    Managing an efficient outpatient clinic can often be complicated by significant no-show rates and escalating appointment lead times. One method that has been proposed for avoiding the wasted capacity due to no-shows is called open or advanced access. The essence of open access is "do today's demand today". We develop a Markov Decision Process (MDP) model that demonstrates that a short booking window does significantly better than open access. We analyze a number of scenarios that explore the trade-off between patient-related measures (lead times) and physician- or system-related measures (revenue, overtime and idle time). Through simulation, we demonstrate that, over a wide variety of potential scenarios and clinics, the MDP policy does as well or better than open access in terms of minimizing costs (or maximizing profits) as well as providing more consistent throughput.

  18. Modeling integrated water user decisions in intermittent supply systems

    Science.gov (United States)

    Rosenberg, David E.; Tarawneh, Tarek; Abdel-Khaleq, Rania; Lund, Jay R.

    2007-07-01

    We apply systems analysis to estimate household water use in an intermittent supply system considering numerous interdependent water user behaviors. Some 39 household actions include conservation; improving local storage or water quality; and accessing sources having variable costs, availabilities, reliabilities, and qualities. A stochastic optimization program with recourse decisions identifies the infrastructure investments and short-term coping actions a customer can adopt to cost-effectively respond to a probability distribution of piped water availability. Monte Carlo simulations show effects for a population of customers. Model calibration reproduces the distribution of billed residential water use in Amman, Jordan. Parametric analyses suggest economic and demand responses to increased availability and alternative pricing. It also suggests potential market penetration for conservation actions, associated water savings, and subsidies to entice further adoption. We discuss new insights to size, target, and finance conservation.

  19. Modeling and Simulation for Enterprise Decision-Making: Successful Projects and Approaches

    DEFF Research Database (Denmark)

    Ramadan, Noha; Ajami, Racha; Mohamed, Nader

    2015-01-01

    Decision-making in enterprises holds different possibilities for profits and risks. Due to the complexity of decision making processes, modeling and simulation tools are being used to facilitate them and minimize the risk of making wrong decisions in the various business process phases....... In this paper, we highlight the role of modeling and simulation in enhancing decision-making processes in enterprises. In addition, we show some techniques that helped enterprises in reaching effective and efficient decisions by adopting modeling and simulation tools....

  20. Modeling and Simulation for Enterprise Decision-Making: Successful Projects and Approaches

    DEFF Research Database (Denmark)

    Ramadan, Noha; Ajami, Racha; Mohamed, Nader

    Decision-making in enterprises holds different possibilities for profits and risks. Due to the complexity of decision making processes, modeling and simulation tools are being used to facilitate them and minimize the risk of making wrong decisions in the various business process phases....... In this paper, we highlight the role of modeling and simulation in enhancing decision-making processes in enterprises. In addition, we show some techniques that helped enterprises in reaching effective and efficient decisions by adopting modeling and simulation tools....

  1. COLLISION AVOIDANCE DECISION- MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

    Institute of Scientific and Technical Information of China (English)

    LU Hong; YI Guodong; TAN Jianrong; LIU Zhenyu

    2008-01-01

    Collision avoidance decision-making models of multiple agents in virtual driving environ- ment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process (AHP) is adopted to establish the agents' collision avoidance decision-making model. To simulate drivers' characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human's thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainty of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

  2. Representing Human Expertise by the OWL Web Ontology Language to Support Knowledge Engineering in Decision Support Systems.

    Science.gov (United States)

    Ramzan, Asia; Wang, Hai; Buckingham, Christopher

    2014-01-01

    Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

  3. A natural human hand model

    NARCIS (Netherlands)

    Van Nierop, O.A.; Van der Helm, A.; Overbeeke, K.J.; Djajadiningrat, T.J.P.

    2007-01-01

    We present a skeletal linked model of the human hand that has natural motion. We show how this can be achieved by introducing a new biology-based joint axis that simulates natural joint motion and a set of constraints that reduce an estimated 150 possible motions to twelve. The model is based on obs

  4. Intelligent Model Management in a Forest Ecosystem Management Decision Support System

    Science.gov (United States)

    Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

    2002-01-01

    Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

  5. Educational Pluralism and Freedom of Religion: Recent Decisions of the European Court of Human Rights

    Science.gov (United States)

    Relano, Eugenia

    2010-01-01

    This paper addresses the sensitive issue of the teaching of religions and beliefs in schools by analysing two recent decisions of the European Court of Human Rights. In these cases, the Court asserts that students should be exempted from compulsory courses on religion or from courses that are not conveyed in an objective, critical and pluralist…

  6. Educational Pluralism and Freedom of Religion: Recent Decisions of the European Court of Human Rights

    Science.gov (United States)

    Relano, Eugenia

    2010-01-01

    This paper addresses the sensitive issue of the teaching of religions and beliefs in schools by analysing two recent decisions of the European Court of Human Rights. In these cases, the Court asserts that students should be exempted from compulsory courses on religion or from courses that are not conveyed in an objective, critical and pluralist…

  7. Human Rights and Decision-Making in Child Protection through Explicit Argumentation

    Science.gov (United States)

    Duffy, Joe; Taylor, Brian; Mc Call, Susannah

    2006-01-01

    A recent judgement in February 2005 by the Lord Chief Justice in Northern Ireland that a Health and Social Services Trust had breached a parent's Article 8 Right to Family Life in the process used to take a young child into care has stimulated major debate about the interface between the Human Rights Act (1998) and professional decision-making in…

  8. Performance of human groups in social foraging: the role of communication in consensus decision making.

    Science.gov (United States)

    King, Andrew J; Narraway, Claire; Hodgson, Lindsay; Weatherill, Aidan; Sommer, Volker; Sumner, Seirian

    2011-04-23

    Early hominids searched for dispersed food sources in a patchy, uncertain environment, and modern humans encounter equivalent spatial-temporal coordination problems on a daily basis. A fundamental, but untested assumption is that our evolved capacity for communication is integral to our success in such tasks, allowing information exchange and consensus decisions based on mutual consideration of pooled information. Here we examine whether communication enhances group performance in humans, and test the prediction that consensus decision-making underlies group success. We used bespoke radio-tagging methodology to monitor the incremental performance of communicating and non-communicating human groups (small group sizes of two to seven individuals), during a social foraging experiment. We found that communicating groups (n = 22) foraged more effectively than non-communicating groups (n = 21) and were able to reach consensus decisions (an 'agreement' on the most profitable foraging resource) significantly more often than non-communicating groups. Our data additionally suggest that gesticulations among group members played a vital role in the achievement of consensus decisions, and therefore highlight the importance of non-verbal signalling of intentions and desires for successful human cooperative behaviour.

  9. Does social capital affect investment in human capital? Family ties and schooling decisions

    NARCIS (Netherlands)

    Di Falco, Salvatore; Bulte, E.H.

    2015-01-01

    We analyse whether traditional sharing norms within kinship networks affect education decisions of poor black households in KwaZulu-Natal. Theory predicts that the size of the kinship network ambiguously impacts on the incentive to invest in human capital (due to opposing ‘empathy’ and ‘free-rider’

  10. Does social capital affect investment in human capital? Family ties and schooling decisions

    NARCIS (Netherlands)

    Falco, Di Salvatore; Bulte, Erwin

    2015-01-01

    We analyse whether traditional sharing norms within kinship networks affect education decisions of poor black households in KwaZulu-Natal. Theory predicts that the size of the kinship network ambiguously impacts on the incentive to invest in human capital (due to opposing ‘empathy’ and ‘free-ride

  11. Connecting Brillouin's principle to a social synergetics probabilistic model. Applications to the binary decision problems

    Science.gov (United States)

    Hubert, Jerzy Z.; Lenda, Andrzej

    2003-08-01

    The presented model takes account of the fact that any decision process-involving choosing at least between two options, in order to be physically realisable, needs to be coupled to some information negentropy source. This is in accordance with Brillouin's Principle (of information). In social decision processes the source of this information negentropy must function in any system that is subject to the decision process. Thermodynamically, such a process can be understood as an inside on-going continuous process of transformation of an internal thermodynamic quantity into informational quantity, or, more precisely: as a transformation of thermodynamic negentropy generated in various metabolic processes going in human body into information negentropy or information tout court. Initial probabilities of selection and choice are defined as in the Weidlich-Haag social synergetics model. Its connection to the negentropy balance equation is made via the traditional quantity, widely used in economics, i.e., the utility value. Thus, in our approach we try to synthesise the Weidlich-Haag social synergetics probabilistic approach with Brillouin's information-thermodynamics method of reasoning. From this model stems an idea of mathematical modelling and physical explanation of one of the basic human and social phenomena: the need of change-change for the sake of change, i.e., without any visible motivations and reasons that would be external to the system. The computations make use of Monte Carlo method in which the time stories of each individual are followed. The results of computations are discussed also in terms of other really observed social phenomena. It seems that the presented method is ample and versatile and can explain-at least qualitatively-many of such phenomena.

  12. Ensemble modelling and structured decision-making to support Emergency Disease Management.

    Science.gov (United States)

    Webb, Colleen T; Ferrari, Matthew; Lindström, Tom; Carpenter, Tim; Dürr, Salome; Garner, Graeme; Jewell, Chris; Stevenson, Mark; Ward, Michael P; Werkman, Marleen; Backer, Jantien; Tildesley, Michael

    2017-03-01

    Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  13. A Reinforcement Learning Model of Precommitment in Decision Making

    Directory of Open Access Journals (Sweden)

    Zeb eKurth-Nelson

    2010-12-01

    Full Text Available Addiction and many other disorders are linked to impulsivity, where a suboptimal choice is preferred when it is immediately available. One solution to impulsivity is precommitment: constraining one's future to avoid being offered a suboptimal choice. A form of impulsivity can be measured experimentally by offering a choice between a smaller reward delivered sooner and a larger reward delivered later. Impulsive subjects are more likely to select the smaller-sooner choice; however, when offered an option to precommit, even impulsive subjects can precommit to the larger-later choice. To precommit or not is a decision between two conditions: (A the original choice (smaller-sooner vs. larger-later, and (B a new condition with only larger-later available. It has been observed that precommitment appears as a consequence of the preference reversal inherent in non-exponential delay-discounting. Here we show that most models of hyperbolic discounting cannot precommit, but a distributed model of hyperbolic discounting does precommit. Using this model, we find (1 faster discounters may be more or less likely than slow discounters to precommit, depending on the precommitment delay, (2 for a constant smaller-sooner versus larger-later preference, a higher ratio of larger reward to smaller reward increases the probability of precommitment, and (3 precommitment is highly sensitive to the shape of the discount curve. These predictions imply that manipulations that alter the discount curve, such as diet or context, may qualitatively affect precommitment.

  14. Using the ACT-R architecture to specify 39 quantitative process models of decision making

    NARCIS (Netherlands)

    Marewski, Julian N.; Mehlhorn, Katja

    Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a

  15. Using the ACT-R architecture to specify 39 quantitative process models of decision making

    NARCIS (Netherlands)

    Marewski, Julian N.; Mehlhorn, Katja

    2011-01-01

    Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a m

  16. A mixed integer program to model spatial wildfire behavior and suppression placement decisions

    Science.gov (United States)

    Erin J. Belval; Yu Wei; Michael. Bevers

    2015-01-01

    Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

  17. Brain networks for exploration decisions utilizing distinct modeled information types during contextual learning.

    Science.gov (United States)

    Wang, Jane X; Voss, Joel L

    2014-06-04

    Exploration permits acquisition of the most relevant information during learning. However, the specific information needed, the influences of this information on decision making, and the relevant neural mechanisms remain poorly understood. We modeled distinct information types available during contextual association learning and used model-based fMRI in conjunction with manipulation of exploratory decision making to identify neural activity associated with information-based decisions. We identified hippocampal-prefrontal contributions to advantageous decisions based on immediately available novel information, distinct from striatal contributions to advantageous decisions based on the sum total available (accumulated) information. Furthermore, network-level interactions among these regions during exploratory decision making were related to learning success. These findings link strategic exploration decisions during learning to quantifiable information and advance understanding of adaptive behavior by identifying the distinct and interactive nature of brain-network contributions to decisions based on distinct information types.

  18. Research on group expandable optimization decision-ms,king model for construction programme choice

    Institute of Scientific and Technical Information of China (English)

    Yan Hongyan

    2012-01-01

    Aiming at the decision-making problem of construction programme choice, this paper advanced a new group expandable optimization decision-making model. Various factors were comprehensively considered, and the new multi- attribute evaluation index system was established. Based on the assumption that decision-makers were rational, this pa- per formed a group of rational preferences through extracting the personal preferences pertinently, so the decision-makers position matrix was determined. The decision-makers position matrix integrated values given by group decision-makers to construction programme comprised a matrix, of which the entropy theory for data mining was adopted in this paper to determine the attribute weights. A decision was made by using the extension decision method. Eventually, the feasibility and practicability of the model were verified by the example.

  19. Optimality and some of its discontents: successes and shortcomings of existing models for binary decisions.

    Science.gov (United States)

    Holmes, Philip; Cohen, Jonathan D

    2014-04-01

    We review how leaky competing accumulators (LCAs) can be used to model decision making in two-alternative, forced-choice tasks, and we show how they reduce to drift diffusion (DD) processes in special cases. As continuum limits of the sequential probability ratio test, DD processes are optimal in producing decisions of specified accuracy in the shortest possible time. Furthermore, the DD model can be used to derive a speed-accuracy trade-off that optimizes reward rate for a restricted class of two alternative forced-choice decision tasks. We review findings that compare human performance with this benchmark, and we reveal both approximations to and deviations from optimality. We then discuss three potential sources of deviations from optimality at the psychological level--avoidance of errors, poor time estimation, and minimization of the cost of control--and review recent theoretical and empirical findings that address these possibilities. We also discuss the role of cognitive control in changing environments and in modulating exploitation and exploration. Finally, we consider physiological factors in which nonlinear dynamics may also contribute to deviations from optimality.

  20. Management decision making for fisher populations informed by occupancy modeling

    Science.gov (United States)

    Fuller, Angela K.; Linden, Daniel W.; Royle, J. Andrew

    2016-01-01

    Harvest data are often used by wildlife managers when setting harvest regulations for species because the data are regularly collected and do not require implementation of logistically and financially challenging studies to obtain the data. However, when harvest data are not available because an area had not previously supported a harvest season, alternative approaches are required to help inform management decision making. When distribution or density data are required across large areas, occupancy modeling is a useful approach, and under certain conditions, can be used as a surrogate for density. We collaborated with the New York State Department of Environmental Conservation (NYSDEC) to conduct a camera trapping study across a 70,096-km2 region of southern New York in areas that were currently open to fisher (Pekania [Martes] pennanti) harvest and those that had been closed to harvest for approximately 65 years. We used detection–nondetection data at 826 sites to model occupancy as a function of site-level landscape characteristics while accounting for sampling variation. Fisher occupancy was influenced positively by the proportion of conifer and mixed-wood forest within a 15-km2 grid cell and negatively associated with road density and the proportion of agriculture. Model-averaged predictions indicated high occupancy probabilities (>0.90) when road densities were low (0.50). Predicted occupancy ranged 0.41–0.67 in wildlife management units (WMUs) currently open to trapping, which could be used to guide a minimum occupancy threshold for opening new areas to trapping seasons. There were 5 WMUs that had been closed to trapping but had an average predicted occupancy of 0.52 (0.07 SE), and above the threshold of 0.41. These areas are currently under consideration by NYSDEC for opening a conservative harvest season. We demonstrate the use of occupancy modeling as an aid to management decision making when harvest-related data are unavailable and when budgetary

  1. How we learn to make decisions: rapid propagation of reinforcement learning prediction errors in humans.

    Science.gov (United States)

    Krigolson, Olav E; Hassall, Cameron D; Handy, Todd C

    2014-03-01

    Our ability to make decisions is predicated upon our knowledge of the outcomes of the actions available to us. Reinforcement learning theory posits that actions followed by a reward or punishment acquire value through the computation of prediction errors-discrepancies between the predicted and the actual reward. A multitude of neuroimaging studies have demonstrated that rewards and punishments evoke neural responses that appear to reflect reinforcement learning prediction errors [e.g., Krigolson, O. E., Pierce, L. J., Holroyd, C. B., & Tanaka, J. W. Learning to become an expert: Reinforcement learning and the acquisition of perceptual expertise. Journal of Cognitive Neuroscience, 21, 1833-1840, 2009; Bayer, H. M., & Glimcher, P. W. Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129-141, 2005; O'Doherty, J. P. Reward representations and reward-related learning in the human brain: Insights from neuroimaging. Current Opinion in Neurobiology, 14, 769-776, 2004; Holroyd, C. B., & Coles, M. G. H. The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709, 2002]. Here, we used the brain ERP technique to demonstrate that not only do rewards elicit a neural response akin to a prediction error but also that this signal rapidly diminished and propagated to the time of choice presentation with learning. Specifically, in a simple, learnable gambling task, we show that novel rewards elicited a feedback error-related negativity that rapidly decreased in amplitude with learning. Furthermore, we demonstrate the existence of a reward positivity at choice presentation, a previously unreported ERP component that has a similar timing and topography as the feedback error-related negativity that increased in amplitude with learning. The pattern of results we observed mirrored the output of a computational model that we implemented to compute reward

  2. IMPORTANCE OF DIFFERENT MODELS IN DECISION MAKING, EXPLAINING THE STRATEGIC BEHAVIOR IN ORGANIZATIONS

    Directory of Open Access Journals (Sweden)

    Cristiano de Oliveira Maciel

    2006-11-01

    Full Text Available This study is about the different models of decision process analyzing the organizational strategy. The article presents the strategy according to a cognitive approach. The discussion about that approach has three models of decision process: rational actor model, organizational behavior, and political model. These models, respectively, present some improvement in the decision making results, search for a good decision facing the cognitive restrictions of the administrator, and lots of talks for making a decision. According to the emphasis of each model, the possibilities for analyzing the strategy are presented. The article also shows that it is necessary to take into account the three different ways of analysis. That statement is justified once the analysis as well as the decision making become more complex, mainly those which are more important for the organizations.

  3. The Role of Intuition in Risk/Benefit Decision-Making in Human Subjects Research.

    Science.gov (United States)

    Resnik, David B

    2017-01-01

    One of the key principles of ethical research involving human subjects is that the risks of research to should be acceptable in relation to expected benefits. Institutional review board (IRB) members often rely on intuition to make risk/benefit decisions concerning proposed human studies. Some have objected to using intuition to make these decisions because intuition is unreliable and biased and lacks transparency. In this article, I examine the role of intuition in IRB risk/benefit decision-making and argue that there are practical and philosophical limits to our ability to reduce our reliance on intuition in this process. The fact that IRB risk/benefit decision-making involves intuition need not imply that it is hopelessly subjective or biased, however, since there are strategies that IRBs can employ to improve their decisions, such as using empirical data to estimate the probability of potential harms and benefits, developing classification systems to guide the evaluation of harms and benefits, and engaging in moral reasoning concerning the acceptability of risks.

  4. Mathematical models of human behavior

    DEFF Research Database (Denmark)

    Møllgaard, Anders Edsberg

    During the last 15 years there has been an explosion in human behavioral data caused by the emergence of cheap electronics and online platforms. This has spawned a whole new research field called computational social science, which has a quantitative approach to the study of human behavior. Most...... studies have considered data sets with just one behavioral variable such as email communication. The Social Fabric interdisciplinary research project is an attempt to collect a more complete data set on human behavior by providing 1000 smartphones with pre-installed data collection software to students...... data set, along with work on other behavioral data. The overall goal is to contribute to a quantitative understanding of human behavior using big data and mathematical models. Central to the thesis is the determination of the predictability of different human activities. Upper limits are derived...

  5. Human-Agent Decision-making: Combining Theory and Practice

    Directory of Open Access Journals (Sweden)

    Sarit Kraus

    2016-06-01

    Full Text Available Extensive work has been conducted both in game theory and logic to model strategic interaction. An important question is whether we can use these theories to design agents for interacting with people? On the one hand, they provide a formal design specification for agent strategies. On the other hand, people do not necessarily adhere to playing in accordance with these strategies, and their behavior is affected by a multitude of social and psychological factors. In this paper we will consider the question of whether strategies implied by theories of strategic behavior can be used by automated agents that interact proficiently with people. We will focus on automated agents that we built that need to interact with people in two negotiation settings: bargaining and deliberation. For bargaining we will study game-theory based equilibrium agents and for argumentation we will discuss logic-based argumentation theory. We will also consider security games and persuasion games and will discuss the benefits of using equilibrium based agents.

  6. Modelling of the costs of decision support for small and medium-sized enterprises

    Directory of Open Access Journals (Sweden)

    Viera Tomišová

    2017-01-01

    Full Text Available The support of decision-making activities in small and medium-sized enterprises (SME has its specific features. When suggesting steps for the implementation of decision-support tools in the enterprise, we identified two main ways of decision-making support based on the data analysis: ERP (Enterprise Resource Planning without BI (Business Intelligence and ERP with BI. In our contribution, we present costs models of both mentioned decision support systems and their practical interpretation.

  7. Handling risk attitudes for preference learning and intelligent decision support

    DEFF Research Database (Denmark)

    Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt

    2015-01-01

    Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...

  8. Model Driven Integrated Decision-Making in Manufacturing Enterprises

    OpenAIRE

    Weston, Richard H.

    2012-01-01

    Decision making requirements and solutions are observed in four world class Manufacturing Enterprises (MEs). Observations made focus on deployed methods of complexity handling that facilitate multi-purpose, distributed decision making. Also observed are examples of partially deficient “integrated decision making” which stem from lack of understanding about how ME structural relations enable and/or constrain reachable ME behaviours. To begin to address this deficiency the paper outlines the us...

  9. The neural processes underlying perceptual decision making in humans: recent progress and future directions.

    Science.gov (United States)

    Kelly, Simon P; O'Connell, Redmond G

    2015-01-01

    In the last two decades, animal neurophysiology research has made great strides towards explaining how the brain can enable adaptive action in the face of noisy sensory information. In particular, this work has identified neural signals that perform the role of a 'decision variable' which integrates sensory information in favor of a particular outcome up to an action-triggering threshold, consistent with long-standing predictions from mathematical psychology. This has provoked an intensive search for similar neural processes at work in the human brain. In this paper we review the progress that has been made in tracing the dynamics of perceptual decision formation in humans using functional imaging and electrophysiology. We highlight some of the limitations that non-invasive recording techniques place on our ability to make definitive judgments regarding the role that specific signals play in decision making. Finally, we provide an overview of our own work in this area which has focussed on two perceptual tasks - intensity change detection and motion discrimination - performed under continuous-monitoring conditions, and highlight the insights gained thus far. We show that through simple paradigm design features such as avoiding sudden intensity transients at evidence onset, a neural instantiation of the theoretical decision variable can be directly traced in the form of a centro-parietal positivity (CPP) in the standard event-related potential (ERP). We recapitulate evidence for the domain-general nature of the CPP process, being divorced from the sensory and motor requirements of the task, and re-plot data of both tasks highlighting this aspect as well as its relationship to decision outcome and reaction time. We discuss the implications of these findings for mechanistically principled research on normal and abnormal decision making in humans.

  10. Perceived Health Benefits and Soy Consumption Behavior: Two-Stage Decision Model Approach

    OpenAIRE

    Moon, Wanki; Balasubramanian, Siva K.; Rimal, Arbindra

    2005-01-01

    A two-stage decision model is developed to assess the effect of perceived soy health benefits on consumers' decisions with respect to soy food. The first stage captures whether or not to consume soy food, while the second stage reflects how often to consume. A conceptual/analytical framework is also employed, combining Lancaster's characteristics model and Fishbein's multi-attribute model. Results show that perceived soy health benefits significantly influence both decision stages. Further, c...

  11. Modeling Evacuate versus Shelter-in-Place Decisions in Wildfires

    Directory of Open Access Journals (Sweden)

    Frank A. Drews

    2011-09-01

    Full Text Available Improving community resiliency to wildfire is a challenging problem in the face of ongoing development in fire-prone regions. Evacuation and shelter-in-place are the primary options for reducing wildfire casualties, but it can be difficult to determine which option offers the most protection in urgent scenarios. Although guidelines and policies have been proposed to inform this decision, a formal approach to evaluating protective options would help advance protective-action theory. We present an optimization model based on the premise that protecting a community can be viewed as assigning threatened households to one of three actions: evacuation, shelter-in-refuge, or shelter-in-home. While evacuation generally offers the highest level of life protection, it can place residents at greater risk when little time is available. This leads to complex trade-offs involving expected fire intensity, available time, and the quality and accessibility of in-place shelter. An application of the model is presented to illustrate a range of issues that can arise across scenarios.

  12. Applications of a simulation model to decisions in mallard management

    Science.gov (United States)

    Cowardin, L.M.; Johnson, D.H.; Shaffer, T.L.; Sparling, D.W.

    1988-01-01

    A system comprising simulation models and data bases for habitat availability and nest success rates was used to predict results from a mallard (Anas platyrhynchos) management plan and to compare six management methods with a control. Individual treatments in the applications included land purchase for waterfowl production, wetland easement purchase, lease of uplands for waterfowl management, cropland retirement, use of no-till winter wheat, delayed cutting of alfalfa, installation of nest baskets, nesting island construction, and use of predator-resistant fencing.The simulations predicted that implementation of the management plan would increase recruits by 24%. Nest baskets were the most effective treatment, accounting for 20.4% of the recruits. No-till winter wheat was the second most effective, accounting for 5.9% of the recruits. Wetland loss due to drainage would cause an 11% loss of breeding population in 10 years.The models were modified to account for migrational homing. The modification indicated that migrational homing would enhance the effects of management. Nest success rates were critical contributions to individual management methods. The most effective treatments, such as nest baskets, had high success rates and affected a large portion of the breeding population.Economic analyses indicated that nest baskets would be the most economical of the three techniques tested. The applications indicated that the system is a useful tool to aid management decisions, but data are scarce for several important variables. Basic research will be required to adequately model the effect of migrational homing and density dependence on production. The comprehensive nature of predictions desired by managers will also require that production models like the one described here be extended to encompass the entire annual cycle of waterfowl.

  13. A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

    Science.gov (United States)

    Zendehrouh, Sareh

    2015-11-01

    Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Bayesian Decision Theory Guiding Educational Decision-Making: Theories, Models and Application

    Science.gov (United States)

    Pan, Yilin

    2016-01-01

    Given the importance of education and the growing public demand for improving education quality under tight budget constraints, there has been an emerging movement to call for research-informed decisions in educational resource allocation. Despite the abundance of rigorous studies on the effectiveness, cost, and implementation of educational…

  15. Control of a Braitenberg Lizard in a Phonotaxis Task with Decision Models

    DEFF Research Database (Denmark)

    Shaikh, Danish; Hallam, John; Christensen-Dalsgaard, Jakob

    2009-01-01

    a Braitenberg vehicle–like mobile robot without any decision model in a phonotaxis task. In this paper we extend the Braitenberg vehicle model to include two separate decision models in the control and recreate the phonotaxis task. We compare the performance of the robot, in terms of successful phonotaxis...

  16. Model requirements for decision support under uncertainty in data scarce dynamic deltas

    NARCIS (Netherlands)

    Haasnoot, Marjolijn; van Deursen, W.P.A.; Kwakkel, J. H.; Middelkoop, H.

    2016-01-01

    There is a long tradition of model-based decision support in water management. The consideration of deep uncertainty, however, changes the requirements imposed on models.. In the face of deep uncertainty, models are used to explore many uncertainties and the decision space across multiple outcomes o

  17. Executable Behavioral Modeling of System and Software Architecture Specifications to Inform Resourcing Decisions

    Science.gov (United States)

    2016-09-01

    BEHAVIORAL MODELING OF SYSTEM- AND SOFTWARE-ARCHITECTURE SPECIFICATIONS TO INFORM RESOURCING DECISIONS by Monica F. Farah-Stapleton...REPORT DATE September 2016 3. REPORT TYPE AND DATES COVERED Doctoral Dissertation 4. TITLE AND SUBTITLE EXECUTABLE BEHAVIORAL MODELING OF SYSTEM...intellectual, programmatic, and organizational resources. Precise behavioral modeling offers a way to assess architectural design decisions prior to

  18. Decision Development in Small Groups I: A Comparison of Two Models.

    Science.gov (United States)

    Poole, Marshall Scott

    1981-01-01

    Studies the sequence of phases in group decision making. Compares the unitary sequence model, which assumes that all groups follow the same sequence of phases, and the multiple sequence model, which assumes that different groups follow different sequences. Results support the latter model and suggest revisions in current decision development. (PD)

  19. ADVISHE: A new tool to report validation of health-economic decision models

    NARCIS (Netherlands)

    Vemer, P.; Corro Ramos, I.; Van Voorn, G.; Al, M.J.; Feenstra, T.L.

    2014-01-01

    Background: Modelers and reimbursement decision makers could both profit from a more systematic reporting of the efforts to validate health-economic (HE) models. Objectives: Development of a tool to systematically report validation efforts of HE decision models and their outcomes. Methods: A gross

  20. Models and theories of prescribing decisions: A review and suggested a new model

    Directory of Open Access Journals (Sweden)

    Ali Murshid M

    2017-06-01

    Full Text Available To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the ‘persuasion theory - elaboration likelihood model’, the stimuli–response marketing model’, the ‘agency theory’, the theory of planned behaviour,’ and ‘social power theory,’ in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research.

  1. Models and theories of prescribing decisions: A review and suggested a new model

    Science.gov (United States)

    Mohaidin, Zurina

    2017-01-01

    To date, research on the prescribing decisions of physician lacks sound theoretical foundations. In fact, drug prescribing by doctors is a complex phenomenon influenced by various factors. Most of the existing studies in the area of drug prescription explain the process of decision-making by physicians via the exploratory approach rather than theoretical. Therefore, this review is an attempt to suggest a value conceptual model that explains the theoretical linkages existing between marketing efforts, patient and pharmacist and physician decision to prescribe the drugs. The paper follows an inclusive review approach and applies the previous theoretical models of prescribing behaviour to identify the relational factors. More specifically, the report identifies and uses several valuable perspectives such as the ‘persuasion theory - elaboration likelihood model’, the stimuli–response marketing model’, the ‘agency theory’, the theory of planned behaviour,’ and ‘social power theory,’ in developing an innovative conceptual paradigm. Based on the combination of existing methods and previous models, this paper suggests a new conceptual model of the physician decision-making process. This unique model has the potential for use in further research. PMID:28690701

  2. Decision models for use with criterion-referenced tests

    NARCIS (Netherlands)

    van der Linden, Willem J.

    1980-01-01

    The problem of mastery decisions and optimizing cutoff scores on criterion-referenced tests is considered. This problem can be formalized as an (empirical) Bayes problem with decisions rules of a monotone shape. Next, the derivation of optimal cutoff scores for threshold, linear, and normal ogive lo

  3. A Gaussian Model of Expert Opinions for Supporting Design Decisions

    NARCIS (Netherlands)

    Rajabalinejad, M.

    2012-01-01

    Decision making in design is of great importance, resulting in success or failure of a system. This paper describes a robust decision support tool for engineering design process, which can be used throughout the design process. The tool is graphical and designed to communicate efficiently with diffe

  4. Hybrid multiple attribute decision making model based on entropy

    Institute of Scientific and Technical Information of China (English)

    Wang Wei; Cui Mingming

    2007-01-01

    From the viewpoint of entropy, this paper investigates a hybrid multiple attribute decision making problem with precision number, interval number and fuzzy number. It defines a new concept: project entropy and the decision is taken according to the values. The validity and scientific nature of the given is proven.

  5. Goal-Programming Model Based on the Utility Function of the Decision-maker

    Institute of Scientific and Technical Information of China (English)

    WANG Zhi-jiang

    2001-01-01

    Based on the analysis of the problems in traditional GP model, this paper provides the model with the utility function of the decision-maker and compares this model with the one presented in reference article [1].

  6. Modeling collective & intelligent decision making of multi-cellular populations.

    Science.gov (United States)

    Shin, Yong-Jun; Mahrou, Bahareh

    2014-01-01

    In the presence of unpredictable disturbances and uncertainties, cells intelligently achieve their goals by sharing information via cell-cell communication and making collective decisions, which are more reliable compared to individual decisions. Inspired by adaptive sensor network algorithms studied in communication engineering, we propose that a multi-cellular adaptive network can convert unreliable decisions by individual cells into a more reliable cell-population decision. It is demonstrated using the effector T helper (a type of immune cell) population, which plays a critical role in initiating immune reactions in response to invading foreign agents (e.g., viruses, bacteria, etc.). While each individual cell follows a simple adaptation rule, it is the combined coordination among multiple cells that leads to the manifestation of "self-organizing" decision making via cell-cell communication.

  7. A Knowledge Model- and Growth Model-Based Decision Support System for Wheat Management

    Institute of Scientific and Technical Information of China (English)

    ZHU Yan; CAO Wei-xing; WANG Qi-meng; TIAN Yong-chao; PAN Jie

    2003-01-01

    By applying the system analysis principle and mathematical modeling technique to knowledge expression system for crop cultural management, the fundamental relationships and quantitative algorithms of wheat growth and management indices to variety types, ecological environments and production levels were analysed and extracted, and a dynamic knowledge model with temporal and spatial characters for wheat management (WheatKnow) was developed. By adopting the soft component characteristics as non language rele vance, re-utilization and portable system maintenance, and by further integrating the wheat growth simulation model (WheatGrow) and intelligent system for wheat management, a comprehensive and digital knowledge model, growth model and component-based decision support system for wheat management (MBDSSWM) was established on the platforms of Visual C++ and Visual Basic. The MBDSSWM realized the effective integration and coupling of the prediction and decision-making functions for digital crop management.

  8. Flexible Bayesian Human Fecundity Models.

    Science.gov (United States)

    Kim, Sungduk; Sundaram, Rajeshwari; Buck Louis, Germaine M; Pyper, Cecilia

    2012-12-01

    Human fecundity is an issue of considerable interest for both epidemiological and clinical audiences, and is dependent upon a couple's biologic capacity for reproduction coupled with behaviors that place a couple at risk for pregnancy. Bayesian hierarchical models have been proposed to better model the conception probabilities by accounting for the acts of intercourse around the day of ovulation, i.e., during the fertile window. These models can be viewed in the framework of a generalized nonlinear model with an exponential link. However, a fixed choice of link function may not always provide the best fit, leading to potentially biased estimates for probability of conception. Motivated by this, we propose a general class of models for fecundity by relaxing the choice of the link function under the generalized nonlinear model framework. We use a sample from the Oxford Conception Study (OCS) to illustrate the utility and fit of this general class of models for estimating human conception. Our findings reinforce the need for attention to be paid to the choice of link function in modeling conception, as it may bias the estimation of conception probabilities. Various properties of the proposed models are examined and a Markov chain Monte Carlo sampling algorithm was developed for implementing the Bayesian computations. The deviance information criterion measure and logarithm of pseudo marginal likelihood are used for guiding the choice of links. The supplemental material section contains technical details of the proof of the theorem stated in the paper, and contains further simulation results and analysis.

  9. Critical infrastructure protection decision support system decision model : overview and quick-start user's guide.

    Energy Technology Data Exchange (ETDEWEB)

    Samsa, M.; Van Kuiken, J.; Jusko, M.; Decision and Information Sciences

    2008-12-01

    The Critical Infrastructure Protection Decision Support System Decision Model (CIPDSS-DM) is a useful tool for comparing the effectiveness of alternative risk-mitigation strategies on the basis of CIPDSS consequence scenarios. The model is designed to assist analysts and policy makers in evaluating and selecting the most effective risk-mitigation strategies, as affected by the importance assigned to various impact measures and the likelihood of an incident. A typical CIPDSS-DM decision map plots the relative preference of alternative risk-mitigation options versus the annual probability of an undesired incident occurring once during the protective life of the investment, assumed to be 20 years. The model also enables other types of comparisons, including a decision map that isolates a selected impact variable and displays the relative preference for the options of interest--parameterized on the basis of the contribution of the isolated variable to total impact, as well as the likelihood of the incident. Satisfaction/regret analysis further assists the analyst or policy maker in evaluating the confidence with which one option can be selected over another.

  10. The Shigella human challenge model.

    Science.gov (United States)

    Porter, C K; Thura, N; Ranallo, R T; Riddle, M S

    2013-02-01

    Shigella is an important bacterial cause of infectious diarrhoea globally. The Shigella human challenge model has been used since 1946 for a variety of objectives including understanding disease pathogenesis, human immune responses and allowing for an early assessment of vaccine efficacy. A systematic review of the literature regarding experimental shigellosis in human subjects was conducted. Summative estimates were calculated by strain and dose. While a total of 19 studies evaluating nine strains at doses ranging from 10 to 1 × 1010 colony-forming units were identified, most studies utilized the S. sonnei strain 53G and the S. flexneri strain 2457T. Inoculum solution and pre-inoculation buffering has varied over time although diarrhoea attack rates do not appear to increase above 75-80%, and dysentery rates remain fairly constant, highlighting the need for additional dose-ranging studies. Expansion of the model to include additional strains from different serotypes will elucidate serotype and strain-specific outcome variability.

  11. Modelling risk aversion to support decision-making for controlling zoonotic livestock diseases

    NARCIS (Netherlands)

    Asseldonk, van M.A.P.M.; Bergevoet, R.H.M.; Ge, L.

    2013-01-01

    Zoonotic infectious livestock diseases are becoming a significant burden for both animal and human health and are rapidly gaining the attention of decision-makers who manage public health programmes. If control decisions have only monetary components, governments are generally regarded as being risk

  12. Network effects in a human capital based economic growth model

    Science.gov (United States)

    Vaz Martins, Teresa; Araújo, Tanya; Augusta Santos, Maria; St Aubyn, Miguel

    2009-06-01

    We revisit a recently introduced agent model [ACS, 11, 99 (2008)], where economic growth is a consequence of education (human capital formation) and innovation, and investigate the influence of the agents’ social network, both on an agent’s decision to pursue education and on the output of new ideas. Regular and random networks are considered. The results are compared with the predictions of a mean field (representative agent) model.

  13. Parents' decision-making about the human papillomavirus vaccine for their daughters: I. Quantitative results.

    Science.gov (United States)

    Krawczyk, Andrea; Knäuper, Bärbel; Gilca, Vladimir; Dubé, Eve; Perez, Samara; Joyal-Desmarais, Keven; Rosberger, Zeev

    2015-01-01

    Vaccination against the human papillomavirus (HPV) is an effective primary prevention measure for HPV-related diseases. For children and young adolescents, the uptake of the vaccine is contingent on parental consent. This study sought to identify key differences between parents who obtain (acceptors) and parents who refuse (non-acceptors) the HPV vaccine for their daughters. In the context of a free, universal, school-based HPV vaccination program in Québec, 774 parents of 9-10 year-old girls completed and returned a questionnaire by mail. The questionnaire was based on the theoretical constructs of the Health Belief Model (HBM), along with constructs from other theoretical frameworks. Of the 774 parents, 88.2% reported their daughter having received the HPV vaccine. Perceived susceptibility of daughters to HPV infection, perceived benefits of the vaccine, perceived barriers (including safety of the vaccine), and cues to action significantly distinguished between parents whose daughters had received the HPV vaccine and those whose daughters had not. Other significant factors associated with daughter vaccine uptake were parents' general vaccination attitudes, anticipated regret, adherence to other routinely recommended vaccines, social norms, and positive media influence. The results of this study identify a number of important correlates related to parents' decisions to accept or refuse the HPV vaccine uptake for their daughters. Future work may benefit from targeting such factors and incorporating other health behavior theories in the design of effective HPV vaccine uptake interventions.

  14. Integrated Model-Based Decisions for Water, Energy and Food Nexus

    Science.gov (United States)

    Zhang, X.; Vesselinov, V. V.

    2015-12-01

    Energy, water and food are critical resources for sustaining social development and human lives; human beings cannot survive without any one of them. Energy crises, water shortages and food security are crucial worldwide problems. The nexus of energy, water and food has received more and more attention in the past decade. Energy, water and food are closely interrelated; water is required in energy development such as electricity generation; energy is indispensable for collecting, treating, and transporting water; both energy and water are crucial inputs for food production. Changes of either of them can lead to substantial impacts on other two resources, and vice versa. Effective decisions should be based on thorough research efforts for better understanding of their complex nexus. Rapid increase of population has significantly intensified the pressures on energy, water and food. Addressing and quantifying their interactive relationships are important for making robust and cost-effective strategies for managing the three resources simultaneously. In addition, greenhouse gases (GHGs) are emitted in energy, water, food production, consequently making contributions to growing climate change. Reflecting environmental impacts of GHGs is also desired (especially, on the quality and quantity of fresh water resources). Thus, a socio-economic model is developed in this study to quantitatively address the complex connections among energy, water and food production. A synthetic problem is proposed to demonstrate the model's applicability and feasibility. Preliminary results related to integrated decisions on energy supply management, water use planning, electricity generation planning, energy facility capacity expansion, food production, and associated GHG emission control are generated for providing cost-effective supports for decision makers.

  15. Multi-Objective Model Checking of Markov Decision Processes

    CERN Document Server

    Etessami, Kousha; Vardi, Moshe Y; Yannakakis, Mihalis

    2008-01-01

    We study and provide efficient algorithms for multi-objective model checking problems for Markov Decision Processes (MDPs). Given an MDP, $M$, and given multiple linear-time ($\\omega$-regular or LTL) properties $\\varphi_i$, and probabilities $r_i \\in [0,1]$, $i=1,...,k$, we ask whether there exists a strategy $\\sigma$ for the controller such that, for all $i$, the probability that a trajectory of $M$ controlled by $\\sigma$ satisfies $\\varphi_i$ is at least $r_i$. We provide an algorithm that decides whether there exists such a strategy and if so produces it, and which runs in time polynomial in the size of the MDP. Such a strategy may require the use of both randomization and memory. We also consider more general multi-objective $\\omega$-regular queries, which we motivate with an application to assume-guarantee compositional reasoning for probabilistic systems. Note that there can be trade-offs between different properties: satisfying property $\\varphi_1$ with high probability may necessitate satisfying $\\var...

  16. Synthetic vision and emotion calculation in intelligent virtual human modeling.

    Science.gov (United States)

    Zhao, Y; Kang, J; Wright, D K

    2007-01-01

    The virtual human technique can already provide vivid and believable human behaviour in more and more scenarios. Virtual humans are expected to replace real humans in hazardous situations to undertake tests and feed back valuable information. This paper will introduce a virtual human with a novel collision-based synthetic vision, short-term memory model and a capability to implement emotion calculation and decision making. The virtual character based on this model can 'see' what is in its field of view (FOV) and remember those objects. After that, a group of affective computing equations have been introduced. These equations have been implemented into a proposed emotion calculation process to enlighten emotion for virtual intelligent humans.

  17. The Application of Time-Delay Dependent H∞ Control Model in Manufacturing Decision Optimization

    Directory of Open Access Journals (Sweden)

    Haifeng Guo

    2015-01-01

    Full Text Available This paper uses a time-delay dependent H∞ control model to analyze the effect of manufacturing decisions on the process of transmission from resources to capability. We establish a theoretical framework of manufacturing management process based on three terms: resource, manufacturing decision, and capability. Then we build a time-delay H∞ robust control model to analyze the robustness of manufacturing management. With the state feedback controller between manufacturing resources and decision, we find that there is an optimal decision to adjust the process of transmission from resources to capability under uncertain environment. Finally, we provide an example to prove the robustness of this model.

  18. The Development of a Normative Acquisition Decision Making Model Incorporating Decision Analysis Principles

    Science.gov (United States)

    1987-09-01

    defined in terms of the functions the manager is responsible for accomplishing. The five functions originally described by Henri Fayol in 1916 are...still used today. The functions of management are planning, organizing, coordinating, commanding (or directing), and controlling. The focus of the Fayol ... Henry ; Raisinghani, Duru; Theoret, Andre. "The Structure of ’Unstructured’ Decision Processes", Administrative Science Quarterly, 21: 246-275 (June 1976

  19. Modeling the Economics of Beach Nourishment Decisions in Response to Coastal Erosion

    Science.gov (United States)

    Ware, M.; Ashton, A. D.; Hoagland, P.; Jin, D.; Kite-Powell, H.; Lorenzo-Trueba, J.

    2012-12-01

    width from nourishment each year. In contrast, for practical nourishment volumes, erosion from accelerating sea-level rise eventually out-competes beach nourishment and inundation occurs. Under the myopic decision-making model, with both constant and accelerating sea-level rise, nourishment does not take place until a property is critically endangered. The beach slope, nourishment volume, property value, and initial beach width all are found to be important factors in determining when nourishment should start and how frequently it should occur thereafter. These models can be used by policy-makers to formulate better coastal management policies, by coastal geologists to understand human impacts on beach dynamics, and by the insurance industry to realistically anticipate human risk-taking and decision-making.

  20. Cortical Network Dynamics of Perceptual Decision-Making in the Human Brain

    Directory of Open Access Journals (Sweden)

    Markus eSiegel

    2011-02-01

    Full Text Available Goal-directed behavior requires the flexible transformation of sensory evidence about our environment into motor actions. Studies of perceptual decision-making have shown that this transformation is distributed across several widely separated brain regions. Yet, little is known about how decision-making emerges from the dynamic interactions among these regions. Here, we review a series of studies, in which we characterized the cortical network interactions underlying a perceptual decision process in the human brain. We used magnetoencephalography (MEG to measure the large-scale cortical population dynamics underlying each of the sub-processes involved in this decision: the encoding of sensory evidence and action plan, the mapping between the two, and the attentional selection of task-relevant evidence. We found that these sub-processes are mediated by neuronal oscillations within specific frequency ranges. Localized gamma-band oscillations in sensory and motor cortices reflect the encoding of the sensory evidence and motor plan. Large-scale oscillations across widespread cortical networks mediate the integrative processes connecting these local networks: Gamma- and beta-band oscillations across frontal, parietal and sensory cortices serve the selection of relevant sensory evidence and its flexible mapping onto action plans. In sum, our results suggest that perceptual decisions are mediated by oscillatory interactions within overlapping local and large-scale cortical networks.

  1. Identifying Tipping Points in a Decision-Theoretic Model of Network Security

    OpenAIRE

    Heimann, C. F. Larry; Nochenson, Alan

    2012-01-01

    Although system administrators are frequently urged to protect the machines in their network, the fact remains that the decision to protect is far from universal. To better understand this decision, we formulate a decision-theoretic model of a system administrator responsible for a network of size n against an attacker attempting to penetrate the network and infect the machines with a virus or similar exploit. By analyzing the model we are able to demonstrate the cost sensitivity of smaller n...

  2. A quantum dynamic belief model to explain the interference effects of categorization on decision making

    OpenAIRE

    He, Zichang; Jiang, Wen

    2017-01-01

    Categorization is necessary for many decision making tasks. However, the categorization process may interfere the decision making result and the law of total probability can be violated in some situations. To predict the interference effect of categorization, some model based on quantum probability has been proposed. In this paper, a new quantum dynamic belief (QDB) model is proposed. Considering the precise decision may not be made during the process, the concept of uncertainty is introduced...

  3. Decision model for evaluating reactor disposition of excess plutonium

    Energy Technology Data Exchange (ETDEWEB)

    Edmunds, T.

    1995-02-01

    The US Department of Energy is currently considering a range of technologies for disposition of excess weapon plutonium. Use of plutonium fuel in fission reactors to generate spent fuel is one class of technology options. This report describes the inputs and results of decision analyses conducted to evaluate four evolutionary/advanced and three existing fission reactor designs for plutonium disposition. The evaluation incorporates multiple objectives or decision criteria, and accounts for uncertainty. The purpose of the study is to identify important and discriminating decision criteria, and to identify combinations of value judgments and assumptions that tend to favor one reactor design over another.

  4. Contextual Risk-based Decision Modeling for Vehicular Networks

    Directory of Open Access Journals (Sweden)

    Vijey Thayananthan

    2016-09-01

    Full Text Available A vehicular ad hoc network (VANET is the emerging technology that allows the drivers to keep the road safety throughout the journey. In VANETs, vehicles can collaborate with each other by exchanging the messages. When these messages are incorrect, drivers will have to face many serious problems which include traffic congestion and minor to fatal road accidents. Therefore, drivers need a method which provides the correct decision using risk analysis calculated from the vehicle context. For this purpose, we propose a new contextual risk-based decision methodology for vehicular networks. This methodology can be used to provide robust and reliable decisions.

  5. Modeling and Analysis in Support of Decision Making for Technological Investment

    Energy Technology Data Exchange (ETDEWEB)

    Lenhart, S

    2003-06-11

    Engineering design, resource allocation, military operations, and investment strategies share a major common trait, which is, to a large extent, independent of their different origins, specific features, and intended goals. The unifying trait is the fact that, in any of these endeavors, one has to make reasonable choices, at multiple levels of decision making, among various possible and sometimes competing prospective solutions to an important and consequential practical problem. While the specifics of the problem depend on application, context, additional constraints, etc., the ultimate--albeit imprecise--goal in all these activities is to ''optimize performance,'' which is to have maximal success/profit/return with minimal time/effort/investment. In general, the underlying system is ruled by complex and often unknown dynamics, and affected by various uncertainties, which are unknown as well; on the other hand, there are numerous levels of decision making, which result in a hierarchical structure in the decision process (tree) that is both asynchronous and non-deterministic. Usually, indifferent of the specific application, as one lowers the level of decision making, alternatives depend on fewer independent variables and models become more detailed and physics/engineering based. On the contrary, at higher levels, various components aggregate and decision making is based more on fuzzier criteria instead of readily quantifiable physics/engineering details. Moreover, decisions are strongly influenced by the educational and personal biases of the people who take them. In some instances, this may blur, if not totally obfuscate objective comparisons between various options. Therefore, a crucial point in decision-making is properly understanding and quantifying the tradeoffs, including all their future relevant consequences. Since the interaction between various choices is an intricate nonlinear process, the focus shifts from the dynamics itself to

  6. A procurement decision model for a video rental store - A case study

    Directory of Open Access Journals (Sweden)

    BJ Kok

    2007-12-01

    Full Text Available A procurement decision model for a video rental store is presented in this paper. The model is based on inventory management, but many classical inventory management principles are inappropriate since the commodities (movie titles are removed from, and after a certain time period, returned to inventory. The commodities also have a decaying demand in general; hence the video rental store owner (the decision maker is required to procure new titles periodically. The question addressed in this paper is how to determine which movie titles to acquire, and how many copies of each in order to best maximise profit. An approximated demand function is presented, and attributes of movie titles in inventory are used to classify candidate movie titles and predict their future demand. This allows the decision maker to select the most profitable candidate items from a list, whilst remaining within a predetermined budget. The procurement decision model is evaluated by means of predicting the expected turnover using the procurement decision model solution, and then comparing it to the turnover achieved using the procurement strategy followed by the store owner. The model is not prescriptive - the decision maker may still utilise his/her experience to acquire new movie titles. The procurement decision model, however, does assist the decision making process by presenting a point of departure from which procurement decisions may be made.

  7. Quantifying the Value of Downscaled Climate Model Information for Adaptation Decisions: When is Downscaling a Smart Decision?

    Science.gov (United States)

    Terando, A. J.; Wootten, A.; Eaton, M. J.; Runge, M. C.; Littell, J. S.; Bryan, A. M.; Carter, S. L.

    2015-12-01

    Two types of decisions face society with respect to anthropogenic climate change: (1) whether to enact a global greenhouse gas abatement policy, and (2) how to adapt to the local consequences of current and future climatic changes. The practice of downscaling global climate models (GCMs) is often used to address (2) because GCMs do not resolve key features that will mediate global climate change at the local scale. In response, the development of downscaling techniques and models has accelerated to aid decision makers seeking adaptation guidance. However, quantifiable estimates of the value of information are difficult to obtain, particularly in decision contexts characterized by deep uncertainty and low system-controllability. Here we demonstrate a method to quantify the additional value that decision makers could expect if research investments are directed towards developing new downscaled climate projections. As a proof of concept we focus on a real-world management problem: whether to undertake assisted migration for an endangered tropical avian species. We also take advantage of recently published multivariate methods that account for three vexing issues in climate impacts modeling: maximizing climate model quality information, accounting for model dependence in ensembles of opportunity, and deriving probabilistic projections. We expand on these global methods by including regional (Caribbean Basin) and local (Puerto Rico) domains. In the local domain, we test whether a high resolution (2km) dynamically downscaled GCM reduces the multivariate error estimate compared to the original coarse-scale GCM. Initial tests show little difference between the downscaled and original GCM multivariate error. When propagated through to a species population model, the Value of Information analysis indicates that the expected utility that would accrue to the manager (and species) if this downscaling were completed may not justify the cost compared to alternative actions.

  8. Human Factors Effecting Forensic Decision Making: Workplace Stress and Well-being.

    Science.gov (United States)

    Jeanguenat, Amy M; Dror, Itiel E

    2017-05-02

    Over the past decade, there has been a growing openness about the importance of human factors in forensic work. However, most of it focused on cognitive bias, and neglected issues of workplace wellness and stress. Forensic scientists work in a dynamic environment that includes common workplace pressures such as workload volume, tight deadlines, lack of advancement, number of working hours, low salary, technology distractions, and fluctuating priorities. However, in addition, forensic scientists also encounter a number of industry-specific pressures, such as technique criticism, repeated exposure to crime scenes or horrific case details, access to funding, working in an adversarial legal system, and zero tolerance for "errors". Thus, stress is an important human factor to mitigate for overall error management, productivity and decision quality (not to mention the well-being of the examiners themselves). Techniques such as mindfulness can become powerful tools to enhance work and decision quality. © 2017 American Academy of Forensic Sciences.

  9. The Value of Human Capital Signals for Investment Decision Making under Uncertainty

    DEFF Research Database (Denmark)

    Hain, Daniel; Christensen, Jesper Lindgaard; Jurowetzki, Roman

    In this paper, we analyze the interaction between human capital signals of entrepreneurial founding teams with the contextual experience of potential investors, aiming to explain investment decision making. We use the case of cross-border venture capital (VC) investments in volatile and uncertain...... experience, investors improve their heuristics and develop more sophisticated and contextual decision making procedures. Previous research in the context of VC investments particularly points at human capital signals of the founding team as an important criteria considered by venture capitalists. Among those...... their less experienced peers. We do so by contrasting cross-border VC investments by the same investors in a selection of sub-Saharan African countries with their investments in European economies. Using a propensity score matching procedure, we match every observed investor-company investment pair...

  10. Development of a model to guide decision making in amyotrophic lateral sclerosis multidisciplinary care.

    Science.gov (United States)

    Hogden, Anne; Greenfield, David; Nugus, Peter; Kiernan, Matthew C

    2015-10-01

    Patients with amyotrophic lateral sclerosis (ALS) face numerous decisions for symptom management and quality of life. Models of decision making in chronic disease and cancer care are insufficient for the complex and changing needs of patients with ALS . The aim was to examine the question: how can decision making that is both effective and patient-centred be enacted in ALS multidisciplinary care? Fifty-four respondents (32 health professionals, 14 patients and eight carers) from two specialized ALS multidisciplinary clinics participated in semi-structured interviews. Interviews were transcribed, coded and analysed thematically. Comparison of stakeholder perspectives revealed six key themes of ALS decision making. These were the decision-making process; patient-centred focus; timing and planning; information sources; engagement with specialized ALS services; and access to non-specialized services. A model, embedded in the specialized ALS multidisciplinary clinic, was derived to guide patient decision making. The model is cyclic, with four stages: 'Participant Engagement'; 'Option Information'; 'Option Deliberation'; and 'Decision Implementation'. Effective and patient-centred decision making is enhanced by the structure of the specialized ALS clinic, which promotes patients' symptom management and quality of life goals. However, patient and carer engagement in ALS decision making is tested by the dynamic nature of ALS, and patient and family distress. Our model optimizes patient-centred decision making, by incorporating patients' cyclic decision-making patterns and facilitating carer inclusion in decision processes. The model captures the complexities of patient-centred decision making in ALS. The framework can assist patients and carers, health professionals, researchers and policymakers in this challenging disease environment. © 2013 John Wiley & Sons Ltd.

  11. Learning to maximize reward rate: a model based on semi-Markov decision processes.

    Science.gov (United States)

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

    2014-01-01

    WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

  12. Procedural Personas for Player Decision Modeling and Procedural Content Generation

    DEFF Research Database (Denmark)

    Holmgård, Christoffer

    2016-01-01

    ." These methods for constructing procedural personas are then integrated with existing procedural content generation systems, acting as critics that shape the output of these systems, optimizing generated content for different personas and by extension, different kinds of players and their decision making styles....... This thesis explores methods for creating low-complexity, easily interpretable, generative AI agents for use in game and simulation design. Based on insights from decision theory and behavioral economics, the thesis investigates how player decision making styles may be defined, operationalised, and measured...... in specific games. It further explores how simple utility functions, easily defined and changed by game designers, can be used to construct agents expressing a variety of decision making styles within a game, using a variety of contemporary AI approaches, naming the resulting agents "Procedural Personas...

  13. Intelligent decision-making models for production and retail operations

    CERN Document Server

    Guo, Zhaoxia

    2016-01-01

    This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.

  14. MEDICAL AND LEGAL ISSUES OF THE DECISIONS RENDERED BY THE EUROPEAN COURT OF HUMAN RIGHTS.

    Science.gov (United States)

    Chakhvadze, B; Chakhvadze, G

    2017-01-01

    The European Convention on Human rights is a document that protects human rights and fundamental freedoms of individuals, and the European Court of Human Rights and its case-law makes a convention a powerful instrument to meet the new challenges of modernity and protect the principles of rule of law and democracy. This is important, particularly for young democracies, including Georgia. The more that Georgia is a party to this convention. Article 3 of the convention deals with torture, inhuman and degrading treatment, while article 8 deals with private life, home and correspondence. At the same time, the international practice of the European court of human rights shows that these articles are often used with regard to medical rights. The paper highlights the most recent and interesting cases from the case-law of the ECHR, in which the courts conclusions are based solely on the European Convention on Human Rights. In most instances, the European Court of Human Rights uses the principle of democracy with regard to medical rights. The European court of human rights considers medical rights as moral underpinning rights. Particularly in every occasion, the European Court of Human Rights acknowledges an ethical dimension of these rights. In most instances, it does not matter whether a plaintiff is a free person or prisoner, the European court of human rights make decisions based on fundamental human rights and freedoms of individuals.

  15. Formal Models of Dilemmas in Social Decision-Making

    Science.gov (United States)

    1974-12-01

    iiapj ■ I" ’""i Unclassified i ■ > v. u ). Ant5-Group Decision Commons Dilemma Competition Cooperation Social Decision-making (PAGE...proposed a simple algebraic structure for the commons dilemma as expounded by Hardin (1960). (This dilemma is based on a somewhat minor point made by...the total wealth has bMlk reduced by 100 lbs., as he., -he wealth of each of the other individuals. This commons dilemma , gain to self with loss

  16. Generation companies decision-making modeling by linear control theory

    Energy Technology Data Exchange (ETDEWEB)

    Gutierrez-Alcaraz, G. [Programa de Graduados e Investigacion en Ingenieria Electrica. Departamento de Ingenieria Electrica y Electronica, Instituto Tecnologico de Morelia. Av. Tecnologico 1500, Col. Lomas de Santiaguito 58120. Morelia, Mich. (Mexico); Sheble, Gerald B. [INESC Porto, Faculdade de Engenharia, Universidade do Porto, Campus da FEUP, Rua Dr. Roberto Frias, 4200-465 Porto (Portugal)

    2010-07-15

    This paper proposes four decision-making procedures to be employed by electric generating companies as part of their bidding strategies when competing in an oligopolistic market: naive, forward, adaptive, and moving average expectations. Decision-making is formulated in a dynamic framework by using linear control theory. The results reveal that interactions among all GENCOs affect market dynamics. Several numerical examples are reported, and conclusions are presented. (author)

  17. A Survey of Enterprise Architecture Analysis Using Multi Criteria Decision Making Models (MCDM)

    Science.gov (United States)

    Zia, Mehmooda Jabeen; Azam, Farooque; Allauddin, Maria

    System design becomes really important for software production due to continuous increase in size and complexity of software systems. It is a complex design activity to build architecture for the systems like large enterprises. Thus it is a critical issue to select the correct architecture in software engineering domain. Moreover, in enterprise architecture selection different goals and objectives must be taken into consideration as it is a multi-criteria decision making problem. Generally this field of enterprise architecture analysis has progressed from the application of linear weighting, through integer programming and linear programming to multi-criteria decision making (MCDM) models. In this paper we survey two multi-criteria decision making models (AHP, ANP) to determine that to what extent they have been used in making powerful decisions in complex enterprise architecture analysis. We have found that by using ANP model, decision makers of an enterprise can make more precise and suitable decisions in selection of enterprise architecture styles.

  18. Simulation modeling to derive the value-of-information for risky animal disease-import decisions.

    Science.gov (United States)

    Disney, W Terry; Peters, Mark A

    2003-11-12

    Simulation modeling can be used in aiding decision-makers in deciding when to invest in additional research and when the risky animal disease-import decision should go forward. Simulation modeling to evaluate value-of-information (VOI) techniques provides a robust, objective and transparent framework for assisting decision-makers in making risky animal and animal product decisions. In this analysis, the hypothetical risk from poultry disease in chicken-meat imports was modeled. Economic criteria were used to quantify alternative confidence-increasing decisions regarding potential import testing and additional research requirements. In our hypothetical example, additional information about poultry disease in the exporting country (either by requiring additional export-flock surveillance that results in no sign of disease, or by conducting additional research into lack of disease transmittal through chicken-meat ingestion) captured >75% of the value-of-information attainable regarding the chicken-meat-import decision.

  19. The Power of Religious Organizations in Human Decision Processes: Analyzing Voting Behavior

    OpenAIRE

    Stadelmann, David; Portmann, Marco; TORGLER, Benno

    2013-01-01

    In Switzerland, two key church institutions - the Conference of Swiss Bishops (CSB) and the Federation of Protestant Churches (FPC) - make public recommendations on how to vote for certain referenda. We leverage this unique situation to directly measure religious organizations' power to shape human decision making. We employ an objective measure of voters' commitment to their religious organization to determine whether they are more likely to vote in line with this organization's recommendati...

  20. Overview 2010 of ARL Program on Network Science for Human Decision Making

    Science.gov (United States)

    2011-01-01

    IN FRACTAL PHYSIOLOGY       OVERVIEW 2010 OF ARL PROGRAM ON NETWORK SCIENCE FOR HUMAN DECISION MAKING   Bruce J West Journal Name: Frontiers in...2:76. doi:10.3389/fphys.2011.00076 Article URL: http://www.frontiersin.org/Journal/Abstract.aspx?s=454& name= fractal %20physiology&ART_DOI=10.3389...functions: transportation, electrical power, food distribution, finance , and health care to name a few. The 1 2 interoperability of these networks

  1. A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

    Directory of Open Access Journals (Sweden)

    Burhanuddin M. A.

    2011-01-01

    Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

  2. Beyond dual-process models: A categorisation of processes underlying intuitive judgement and decision making

    NARCIS (Netherlands)

    Glöckner, A.; Witteman, C.L.M.

    2010-01-01

    Intuitive-automatic processes are crucial for making judgements and decisions. The fascinating complexity of these processes has attracted many decision researchers, prompting them to start investigating intuition empirically and to develop numerous models. Dual-process models assume a clear distinc

  3. PRESCRIPTIVE MODEL FOR THE STRATEGIC DECISION-MAKING PROCESSES FROM THE ROMANIAN ENTERPRISES

    Directory of Open Access Journals (Sweden)

    Razvan STEFANESCU

    2005-01-01

    Full Text Available This paper proposes a prescriptive model for the strategic decision-making from the Romanianenterprises. Within the paper there will be described the phases implied in solving a strategicproblem. Finally, there will be presented a strategic decision from a Romanian enterprise, elaboratedon the base of the model.

  4. Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments

    Science.gov (United States)

    Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.

    2009-01-01

    The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…

  5. Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments

    Science.gov (United States)

    Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.

    2009-01-01

    The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…

  6. A new validation-assessment tool for health-economic decision models

    NARCIS (Netherlands)

    Mauskopf, J.; Vemer, P.; Voorn, van G.A.K.; Corro Ramos, I.

    2014-01-01

    A validation-assessment tool is being developed for decision makers to transparently and consistently evaluate the validation status of different health-economic decision models. It is designed as a list of validation techniques covering all relevant aspects of model validation to be filled in by

  7. A Review of Contemporary Ethical Decision-Making Models for Mental Health Professionals

    Science.gov (United States)

    Francis, Perry C.

    2015-01-01

    Mental health professionals are faced with increasingly complex ethical decisions that are impacted by culture, personal and professional values, and the contexts in which they and their clients inhabit. This article presents the reasons for developing and implementing multiple ethical decision making models and reviews four models that address…

  8. An integrated ethical approach to bioethical decision-making: A proposed model for ministers

    Directory of Open Access Journals (Sweden)

    Magdalena C. de Lange

    2012-09-01

    Full Text Available This article outlined a model for guidance in ‘doing’ bioethics in a Reformed context. The proposed model suggested that in order to arrive at responsible ethical decisions, one must refer to both contextual elements and theory. The theoretical grounding for this model was based on the integration of a deontological and virtue ethics approach, arguing that virtue enables persons to know and desire the right moral ends and motivates them to carry out appropriate action toward achieving these ends. An integrative model opens up the possibility whereby bioethics as a systematic tool provides the individual decision-maker with the critical-reflective skills and justification for the ultimate choice that is lacking in the general decision-making processes. This could lead to clearer thinking and increased confidence in the justification of decisions within the Reformed tradition. The proposed hermeneutical perspective on ethical decision-making represents a shift in views about the nature of knowledge and the process of how we come to know. The key to this hermeneutical approach is to acknowledge the dialectic between the universal and the subjectivity of human relations. Working in specific religious communities, one needs to take cognisance of the fact that knowledge is situated in the context of human relationships in which the interpreter participates when articulating the meaning of bioethical experiences. Another aspect that is anticipated lies in the realisation that people struggling with bioethical dilemmas should not be viewed as isolated individuals, but as members of a broader faith community.‘n Geïntegreerde etiese benadering tot bioetiese besluitneming: Voorgestelde model vir predikante. Hierdie artikel het ‘n model geskets wat moontlike riglyne aantoon vir die  beoefening  van  bioetiek  binne  ‘n  Gereformeerde  konteks.  Die  voorgestelde  model argumenteer dat verwysing na beide kontekstuele elemente en teorie

  9. Results from evaluations of models and cost-effectiveness tools to support introduction decisions for new vaccines need critical appraisal

    Directory of Open Access Journals (Sweden)

    Moorthy Vasee

    2011-05-01

    Full Text Available Abstract The World Health Organization (WHO recommends that the cost-effectiveness (CE of introducing new vaccines be considered before such a programme is implemented. However, in low- and middle-income countries (LMICs, it is often challenging to perform and interpret the results of model-based economic appraisals of vaccines that benefit from locally relevant data. As a result, WHO embarked on a series of consultations to assess economic analytical tools to support vaccine introduction decisions for pneumococcal, rotavirus and human papillomavirus vaccines. The objectives of these assessments are to provide decision makers with a menu of existing CE tools for vaccines and their characteristics rather than to endorse the use of a single tool. The outcome will provide policy makers in LMICs with information about the feasibility of applying these models to inform their own decision making. We argue that if models and CE analyses are used to inform decisions, they ought to be critically appraised beforehand, including a transparent evaluation of their structure, assumptions and data sources (in isolation or in comparison to similar tools, so that decision makers can use them while being fully aware of their robustness and limitations.

  10. Modelling the learning of biomechanics and visual planning for decision-making of motor actions.

    Science.gov (United States)

    Cos, Ignasi; Khamassi, Mehdi; Girard, Benoît

    2013-11-01

    Recent experiments showed that the bio-mechanical ease and end-point stability associated to reaching movements are predicted prior to movement onset, and that these factors exert a significant influence on the choice of movement. As an extension of these results, here we investigate whether the knowledge about biomechanical costs and their influence on decision-making are the result of an adaptation process taking place during each experimental session or whether this knowledge was learned at an earlier stage of development. Specifically, we analysed both the pattern of decision-making and its fluctuations during each session, of several human subjects making free choices between two reaching movements that varied in path distance (target relative distance), biomechanical cost, aiming accuracy and stopping requirement. Our main result shows that the effect of biomechanics is well established at the start of the session, and that, consequently, the learning of biomechanical costs in decision-making occurred at an earlier stage of development. As a means to characterise the dynamics of this learning process, we also developed a model-based reinforcement learning model, which generates a possible account of how biomechanics may be incorporated into the motor plan to select between reaching movements. Results obtained in simulation showed that, after some pre-training corresponding to a motor babbling phase, the model can reproduce the subjects' overall movement preferences. Although preliminary, this supports that the knowledge about biomechanical costs may have been learned in this manner, and supports the hypothesis that the fluctuations observed in the subjects' behaviour may adapt in a similar fashion. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Parent-son decision-making about human papillomavirus vaccination: a qualitative analysis

    Directory of Open Access Journals (Sweden)

    Alexander Andreia B

    2012-12-01

    Full Text Available Abstract Background Licensed for use in males in 2009, Human Papillomavirus (HPV vaccination rates in adolescent males are extremely low. Literature on HPV vaccination focuses on females, adult males, or parents of adolescent males, without including adolescent males or the dynamics of the parent-son interaction that may influence vaccine decision-making. The purpose of this paper is to examine the decision-making process of parent-son dyads when deciding whether or not to get vaccinated against HPV. Methods Twenty-one adolescent males (ages 13–17, with no previous HPV vaccination, and their parents/guardians were recruited from adolescent primary care clinics serving low to middle income families in a large Midwestern city. Dyad members participated in separate semi-structured interviews assessing the relative role of the parent and son in the decision regarding HPV vaccination. Interviews were recorded, transcribed, and coded using inductive content analysis. Results Parents and sons focused on protection as a reason for vaccination; parents felt a need to protect their child, while sons wanted to protect their own health. Parents and sons commonly misinterpreted the information about the vaccine. Sons were concerned about an injection in the penis, while some parents and sons thought the vaccine would protect them against other sexually transmitted infections including Herpes, Gonorrhea, and HIV. Parents and sons recalled that the vaccine prevented genital warts rather than cancer. The vaccine decision-making process was rapid and dynamic, including an initial reaction to the recommendation for HPV vaccine, discussion between parent and son, and the final vaccine decision. Provider input was weighed in instances of initial disagreement. Many boys felt that this was the first health care decision that they had been involved in. Dyads which reported shared decision-making were more likely to openly communicate about sexual issues than those

  12. Opinion:the use of natural hazard modeling for decision making under uncertainty

    Institute of Scientific and Technical Information of China (English)

    David E Calkin; Mike Mentis

    2015-01-01

    Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex environmental models. However, to our knowledge there has been less focus on the conditions where decision makers can confidently rely on results from these models. In this review we propose a preliminary set of conditions necessary for the appropriate application of modeled results to natural hazard decision making and provide relevant examples within US wildfire management programs.

  13. Effective decision-making model for hi-tech new product development

    Institute of Scientific and Technical Information of China (English)

    王哲; 于渤; 徐殿国

    2003-01-01

    In order to identify the effective decision-making factors at the individual NPD project manager level,a new effective decision-making model has been established by introducing the concept of decision-making effectiveness, analyzing the role of expertise, and identifying the major role of expertise and insight with respect to the interfaces between a new product, an organization, customers, technologies and regulations, for the study of the effective decision-making facilitators and inhibitors for a NPD project. The analysis of the unique task conditions for individual decision-makers shows that perceived complexity, uncertainty and time pressure have their negative effect on the effective decision-making process. It is concluded that the flexible, balanced and appropriate use of rational analysis, common sense and intuition is a key effective decision-making factor, and the task conditions.

  14. A Comparison between Mechanisms of Multi-Alternative Perceptual Decision Making: Ability to Explain Human Behavior, Predictions for Neurophysiology, and Relationship with Decision Theory.

    Science.gov (United States)

    Ditterich, Jochen

    2010-01-01

    While there seems to be relatively wide agreement about perceptual decision making relying on integration-to-threshold mechanisms, proposed models differ in a variety of details. This study compares a range of mechanisms for multi-alternative perceptual decision making, including integration with and without leakage, feedforward and feedback inhibition for mediating the competition between integrators, as well as linear and non-linear mechanisms for combining signals across alternatives. It is shown that a number of mechanisms make very similar predictions for the decision behavior and are therefore able to explain previously published data from a multi-alternative perceptual decision task. However, it is also demonstrated that the mechanisms differ in their internal dynamics and therefore make different predictions for neuorphysiological experiments. The study further addresses the relationship of these mechanisms with decision theory and statistical testing and analyzes their optimality.

  15. A multicriteria decision making model for assessment and selection of an ERP in a logistics context

    Science.gov (United States)

    Pereira, Teresa; Ferreira, Fernanda A.

    2017-07-01

    The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

  16. A decision-directed approach for prioritizing research into the impact of nanomaterials on the environment and human health

    Science.gov (United States)

    Linkov, Igor; Bates, Matthew E.; Canis, Laure J.; Seager, Thomas P.; Keisler, Jeffrey M.

    2011-12-01

    The emergence of nanotechnology has coincided with an increased recognition of the need for new approaches to understand and manage the impact of emerging technologies on the environment and human health. Important elements in these new approaches include life-cycle thinking, public participation and adaptive management of the risks associated with emerging technologies and new materials. However, there is a clear need to develop a framework for linking research on the risks associated with nanotechnology to the decision-making needs of manufacturers, regulators, consumers and other stakeholder groups. Given the very high uncertainties associated with nanomaterials and their impact on the environment and human health, research resources should be directed towards creating the knowledge that is most meaningful to these groups. Here, we present a model (based on multi-criteria decision analysis and a value of information approach) for prioritizing research strategies in a way that is responsive to the recommendations of recent reports on the management of the risk and impact of nanomaterials on the environment and human health.

  17. A decision-directed approach for prioritizing research into the impact of nanomaterials on the environment and human health.

    Science.gov (United States)

    Linkov, Igor; Bates, Matthew E; Canis, Laure J; Seager, Thomas P; Keisler, Jeffrey M

    2011-10-02

    The emergence of nanotechnology has coincided with an increased recognition of the need for new approaches to understand and manage the impact of emerging technologies on the environment and human health. Important elements in these new approaches include life-cycle thinking, public participation and adaptive management of the risks associated with emerging technologies and new materials. However, there is a clear need to develop a framework for linking research on the risks associated with nanotechnology to the decision-making needs of manufacturers, regulators, consumers and other stakeholder groups. Given the very high uncertainties associated with nanomaterials and their impact on the environment and human health, research resources should be directed towards creating the knowledge that is most meaningful to these groups. Here, we present a model (based on multi-criteria decision analysis and a value of information approach) for prioritizing research strategies in a way that is responsive to the recommendations of recent reports on the management of the risk and impact of nanomaterials on the environment and human health.

  18. Using the ACT-R architecture to specify 39 quantitative process models of decision making

    Directory of Open Access Journals (Sweden)

    Julian N. Marewski

    2011-08-01

    Full Text Available Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a methodological primer on how detailed cognitive architectures such as ACT-R allow remedying these problems. To make our point, we address a controversy, namely, whether noncompensatory or compensatory processes better describe how people make decisions from the accessibility of memories. We specify 39 models of accessibility-based decision processes in ACT-R, including the noncompensatory recognition heuristic and various other popular noncompensatory and compensatory decision models. Additionally, to illustrate how such models can be tested, we conduct a model comparison, fitting the models to one experiment and letting them generalize to another. Behavioral data are best accounted for by race models. These race models embody the noncompensatory recognition heuristic and compensatory models as a race between competing processes, dissolving the dichotomy between existing decision models.

  19. Trends in control and decision-making for human-robot collaboration systems

    CERN Document Server

    Zhang, Fumin

    2017-01-01

    This book provides an overview of recent research developments in the automation and control of robotic systems that collaborate with humans. A measure of human collaboration being necessary for the optimal operation of any robotic system, the contributors exploit a broad selection of such systems to demonstrate the importance of the subject, particularly where the environment is prone to uncertainty or complexity. They show how such human strengths as high-level decision-making, flexibility, and dexterity can be combined with robotic precision, and ability to perform task repetitively or in a dangerous environment. The book focuses on quantitative methods and control design for guaranteed robot performance and balanced human experience. Its contributions develop and expand upon material presented at various international conferences. They are organized into three parts covering: one-human–one-robot collaboration; one-human–multiple-robot collaboration; and human–swarm collaboration. Individual topic ar...

  20. MODELING HUMAN COMPREHENSION OF DATA VISUALIZATIONS.

    Energy Technology Data Exchange (ETDEWEB)

    Matzen, Laura E.; Haass, Michael Joseph; Divis, Kristin Marie; Wilson, Andrew T.

    2017-09-01

    This project was inspired by two needs. The first is a need for tools to help scientists and engineers to design effective data visualizations for communicating information, whether to the user of a system, an analyst who must make decisions based on complex data, or in the context of a technical report or publication. Most scientists and engineers are not trained in visualization design, and they could benefit from simple metrics to assess how well their visualization's design conveys the intended message. In other words, will the most important information draw the viewer's attention? The second is the need for cognition-based metrics for evaluating new types of visualizations created by researchers in the information visualization and visual analytics communities. Evaluating visualizations is difficult even for experts. However, all visualization methods and techniques are intended to exploit the properties of the human visual system to convey information efficiently to a viewer. Thus, developing evaluation methods that are rooted in the scientific knowledge of the human visual system could be a useful approach. In this project, we conducted fundamental research on how humans make sense of abstract data visualizations, and how this process is influenced by their goals and prior experience. We then used that research to develop a new model, the Data Visualization Saliency Model, that can make accurate predictions about which features in an abstract visualization will draw a viewer's attention. The model is an evaluation tool that can address both of the needs described above, supporting both visualization research and Sandia mission needs.

  1. The UNITE-DSS Modelling System: Risk Simulation and Decision Conferencing

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Barfod, Michael Bruhn

    This presentation introduces the brand new approach of integrating risk simulation and decision conferencing within transport project appraisal (UNITE-DSS model). The modelling approach is divided into various modules respectively as point estimates (cost-benefit analysis), stochastic interval...

  2. Models for Rational Decision Making. Analysis of Literature and Selected Bibliography. Analysis and Bibliography Series, No. 6.

    Science.gov (United States)

    Hall, John S.

    This review analyzes the trend in educational decision making to replace hierarchical authority structures with more rational models for decision making drawn from management science. Emphasis is also placed on alternatives to a hierarchical decision-making model, including governing models, union models, and influence models. A 54-item…

  3. Modeling of Human Joint Structures.

    Science.gov (United States)

    1982-09-01

    Radial Lateral " epicondyle Olecranon Radius Ulna Figure 3. Lateral aspect of the right elbow joint. -17- Annular Ligament This strong band encircles... elbow joint, knee joint, human joints, shoulder joint, ankle joint, joint models, hip joint, ligaments. 20. ABSTRACT (Continue on reverse side If...ligaments. -A rather extended discussion of the articulations and anatomical descriptions of the elbow , shoulder, hip, knee and ankle joints are

  4. Decision-Making Models with Sets of Strategies for Applications to Individuals and Groups in Higher Education.

    Science.gov (United States)

    Gill, Wanda E.

    Three decision-making models that have applications for college presidents and administrators are reviewed. While both individual and group decision-making are addressed, emphasis is placed on the importance of group decisions on institutional policy planning. The model of Edmund M. Burke (1979) presents specific decision-making strategies in…

  5. Decision making under uncertainty in a spiking neural network model of the basal ganglia.

    Science.gov (United States)

    Héricé, Charlotte; Khalil, Radwa; Moftah, Marie; Boraud, Thomas; Guthrie, Martin; Garenne, André

    2016-12-01

    The mechanisms of decision-making and action selection are generally thought to be under the control of parallel cortico-subcortical loops connecting back to distinct areas of cortex through the basal ganglia and processing motor, cognitive and limbic modalities of decision-making. We have used these properties to develop and extend a connectionist model at a spiking neuron level based on a previous rate model approach. This model is demonstrated on decision-making tasks that have been studied in primates and the electrophysiology interpreted to show that the decision is made in two steps. To model this, we have used two parallel loops, each of which performs decision-making based on interactions between positive and negative feedback pathways. This model is able to perform two-level decision-making as in primates. We show here that, before learning, synaptic noise is sufficient to drive the decision-making process and that, after learning, the decision is based on the choice that has proven most likely to be rewarded. The model is then submitted to lesion tests, reversal learning and extinction protocols. We show that, under these conditions, it behaves in a consistent manner and provides predictions in accordance with observed experimental data.

  6. A Markov Decision Process Model for Cervical Cancer Screening Policies in Colombia.

    Science.gov (United States)

    Akhavan-Tabatabaei, Raha; Sánchez, Diana Marcela; Yeung, Thomas G

    2017-02-01

    Cervical cancer is the second most common cancer in women around the world, and the human papillomavirus (HPV) is universally known as the necessary agent for developing this disease. Through early detection of abnormal cells and HPV virus types, cervical cancer incidents can be reduced and disease progression prevented. We propose a finite-horizon Markov decision process model to determine the optimal screening policies for cervical cancer prevention. The optimal decision is given in terms of when and what type of screening test to be performed on a patient based on her current diagnosis, age, HPV contraction risk, and screening test results. The cost function considers the tradeoff between the cost of prevention and treatment procedures and the risk of taking no action while taking into account a cost assigned to loss of life quality in each state. We apply the model to data collected from a representative sample of 1141 affiliates at a health care provider located in Bogotá, Colombia. To track the disease incidence more effectively and avoid higher cancer rates and future costs, the optimal policies recommend more frequent colposcopies and Pap tests for women with riskier profiles.

  7. High-frequency oscillations in distributed neural networks reveal the dynamics of human decision making

    Directory of Open Access Journals (Sweden)

    Adrian G Guggisberg

    2008-03-01

    Full Text Available We examine the relative timing of numerous brain regions involved in human decisions that are based on external criteria, learned information, personal preferences, or unconstrained internal considerations. Using magnetoencephalography (MEG and advanced signal analysis techniques, we were able to non-invasively reconstruct oscillations of distributed neural networks in the high-gamma frequency band (60–150 Hz. The time course of the observed neural activity suggested that two-alternative forced choice tasks are processed in four overlapping stages: processing of sensory input, option evaluation, intention formation, and action execution. Visual areas are activated fi rst, and show recurring activations throughout the entire decision process. The temporo-occipital junction and the intraparietal sulcus are active during evaluation of external values of the options, 250–500 ms after stimulus presentation. Simultaneously, personal preference is mediated by cortical midline structures. Subsequently, the posterior parietal and superior occipital cortices appear to encode intention, with different subregions being responsible for different types of choice. The cerebellum and inferior parietal cortex are recruited for internal generation of decisions and actions, when all options have the same value. Action execution was accompanied by activation peaks in the contralateral motor cortex. These results suggest that high-gamma oscillations as recorded by MEG allow a reliable reconstruction of decision processes with excellent spatiotemporal resolution.

  8. Temporal characteristics of the influence of punishment on perceptual decision making in the human brain.

    Science.gov (United States)

    Blank, Helen; Biele, Guido; Heekeren, Hauke R; Philiastides, Marios G

    2013-02-27

    Perceptual decision making is the process by which information from sensory systems is combined and used to influence our behavior. In addition to the sensory input, this process can be affected by other factors, such as reward and punishment for correct and incorrect responses. To investigate the temporal dynamics of how monetary punishment influences perceptual decision making in humans, we collected electroencephalography (EEG) data during a perceptual categorization task whereby the punishment level for incorrect responses was parametrically manipulated across blocks of trials. Behaviorally, we observed improved accuracy for high relative to low punishment levels. Using multivariate linear discriminant analysis of the EEG, we identified multiple punishment-induced discriminating components with spatially distinct scalp topographies. Compared with components related to sensory evidence, components discriminating punishment levels appeared later in the trial, suggesting that punishment affects primarily late postsensory, decision-related processing. Crucially, the amplitude of these punishment components across participants was predictive of the size of the behavioral improvements induced by punishment. Finally, trial-by-trial changes in prestimulus oscillatory activity in the alpha and gamma bands were good predictors of the amplitude of these components. We discuss these findings in the context of increased motivation/attention, resulting from increases in punishment, which in turn yields improved decision-related processing.

  9. Decision-Theoretical Navigation of Service Robots Using POMDPs with Human-Robot Co-Occurrence Prediction

    Directory of Open Access Journals (Sweden)

    Kun Qian

    2013-02-01

    Full Text Available To improve the natural human‐avoidance skills of service robots, a human motion predictive navigation method is proposed, namely PN‐POMDP. A human‐robot motion co‐occurrence estimation algorithm is proposed which incorporates long‐term and short‐term human motion prediction. To improve the reliability of probabilistic and predictive navigation, the POMDP model is utilized to generate navigation control policies through theoretically optimal decisions. A layered motion control structure is proposed that combines global path planning and reactive avoidance. Multiple comity policies are integrated with a decision‐making module that generates efficient and human‐compliant navigational behaviours for robots. Experimental results illustrate the effectiveness and reliability of the predictive navigation method.

  10. An interval number-based multiple attribute bid-decision making model for substation equipments

    Directory of Open Access Journals (Sweden)

    Zhu Lili

    2016-01-01

    Full Text Available By analyzing the characteristics of public bidding for substation equipments and combining with the research methods of multiple attribute decision-making problems, a multiple attribute bid-decision making model is presented. Firstly, the weight of interval numbers is specified by using the interval numbers theory and entropy theory. Secondly, the deviation degree of decision-making scheme is proposed. Then the schemes are sorted. A typical case is analyzed based on the above-mentioned.

  11. Game Theory Model and Equilibrium Analysis of Peasant's Production Decision

    Institute of Scientific and Technical Information of China (English)

    Qi Xue-lian; Zhang Ya-zhuo; Meng Jun

    2012-01-01

    Unbalanced agricultural production decision becomes the great block that influences the effective distribution of social resources, national grain security, social stability and economic development. This paper took the game theory as an analyzed tool to describe the interactional processes among the peasants, and set up the game theory model of independent decision and joint decision by peasants. It was shown that the government's positive guide and the market environment macroscopically controlled by the government could effectively increased the peasants' income

  12. Procedural Personas for Player Decision Modeling and Procedural Content Generation

    DEFF Research Database (Denmark)

    Holmgård, Christoffer

    2016-01-01

    in specific games. It further explores how simple utility functions, easily defined and changed by game designers, can be used to construct agents expressing a variety of decision making styles within a game, using a variety of contemporary AI approaches, naming the resulting agents "Procedural Personas......." These methods for constructing procedural personas are then integrated with existing procedural content generation systems, acting as critics that shape the output of these systems, optimizing generated content for different personas and by extension, different kinds of players and their decision making styles...

  13. A dynamic decision model for portfolio investment and assets management

    Institute of Scientific and Technical Information of China (English)

    QIAN Edward Y.; FENG Ying; HIGGISION James

    2005-01-01

    This paper addresses a dynamic portfolio investment problem. It discusses how we can dynamically choose candidate assets, achieve the possible maximum revenue and reduce the risk to the minimum level. The paper generalizes Markowitz's portfolio selection theory and Sharpe's rule for investment decision. An analytical solution is presented to show how an institutional or individual investor can combine Markowitz's portfolio selection theory, generalized Sharpe's rule and Value-at-Risk(VaR) to find candidate assets and optimal level of position sizes for investment (dis-investment). The result shows that the generalized Markowitz's portfolio selection theory and generalized Sharpe's rule improve decision making for investment.

  14. Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms.

    Science.gov (United States)

    List, Christian; Elsholtz, Christian; Seeley, Thomas D

    2009-03-27

    Condorcet's jury theorem shows that when the members of a group have noisy but independent information about what is best for the group as a whole, majority decisions tend to outperform dictatorial ones. When voting is supplemented by communication, however, the resulting interdependencies between decision makers can strengthen or undermine this effect: they can facilitate information pooling, but also amplify errors. We consider an intriguing non-human case of independent information pooling combined with communication: the case of nest-site choice by honeybee (Apis mellifera) swarms. It is empirically well documented that when there are different nest sites that vary in quality, the bees usually choose the best one. We develop a new agent-based model of the bees' decision process and show that its remarkable reliability stems from a particular interplay of independence and interdependence between the bees.

  15. Increasing Social–Ecological Resilience by Placing Science at the Decision Table: the Role of the San Pedro Basin (Arizona Decision-Support System Model

    Directory of Open Access Journals (Sweden)

    Tim Finan

    2009-06-01

    Full Text Available We have analyzed how the collaborative development process of a decision-support system (DSS model can effectively contribute to increasing the resilience of regional social–ecological systems. In particular, we have focused on the case study of the transboundary San Pedro Basin, in the Arizona-Sonora desert region. This is a semi-arid watershed where water is a scarce resource used to cover competing human and environmental needs. We have outlined the essential traits in the development of the decision-support process that contributed to an improvement of water-resources management capabilities while increasing the potential for consensual problem solving. Comments and feedback from the stakeholders benefiting from the DSS in the San Pedro Basin are presented and analyzed within the regional (United States–Mexico boundary, social, and institutional context. We have indicated how multidisciplinary collaboration between academia and stakeholders can be an effective step toward collaborative management. Such technology transfer and capacity building provides a common arena for testing water-management policies and evaluating future scenarios. Putting science at the service of a participatory decision-making process can provide adaptive capacity to accommodate future change (i.e., building resilience in the management system.

  16. From Performance to Decision Processes in 33 Years: A History of Organizational Behavior and Human Decision Processes under James C. Naylor.

    Science.gov (United States)

    Weber

    1998-12-01

    For the past 33 years, Organizational Behavior and Human Decision Processes has thrived under a single editor. That editor, James C. Naylor, is retiring from his long stewardship. This article chronicles the course of the journal under Jim's direction and marks some of the accomplishments and changes over the past three decades that go to his credit. Copyright 1998 Academic Press.

  17. A human factors engineering approach to biomedical decision making: A new role for automatic target recognizer technologies

    Energy Technology Data Exchange (ETDEWEB)

    Sobel, A.L.; Stalker, K.T.; Yee, A.

    1995-01-01

    This report identifies the key features noted as requirements in the diagnostic decision-making process of Single Photon Emission Computed Tomography (SPECT) cardiac imaging. The report discusses the critical issues that create the basic system framework for design of an automatic target recognizer (ATR) algorithm prototype to support diagnosis of coronary artery disease. Candidate feature discovery algorithms that may form the basis of future work include Adaptive Resonance Theory and Bayesian Decision Network. A framework for the practitioner-Human-System-Interface would include baseline patient history and demographic data; reference cardiac imagery history; and current overlay imagery to provide complementary information (i.e., coronary angiography, echocardiography, and SPECT images). The goal is to design a prototype that would represent a fused present and historical {open_quotes}whole{close_quotes} functional, structural, and physiologic cardiac patient model. This framework decision-assisting platform would be available to practitioner and student alike, with no {open_quotes}real-world{close_quotes} consequences.

  18. EEG-fMRI based information theoretic characterization of the human perceptual decision system.

    Directory of Open Access Journals (Sweden)

    Dirk Ostwald

    Full Text Available The modern metaphor of the brain is that of a dynamic information processing device. In the current study we investigate how a core cognitive network of the human brain, the perceptual decision system, can be characterized regarding its spatiotemporal representation of task-relevant information. We capitalize on a recently developed information theoretic framework for the analysis of simultaneously acquired electroencephalography (EEG and functional magnetic resonance imaging data (fMRI (Ostwald et al. (2010, NeuroImage 49: 498-516. We show how this framework naturally extends from previous validations in the sensory to the cognitive domain and how it enables the economic description of neural spatiotemporal information encoding. Specifically, based on simultaneous EEG-fMRI data features from n = 13 observers performing a visual perceptual decision task, we demonstrate how the information theoretic framework is able to reproduce earlier findings on the neurobiological underpinnings of perceptual decisions from the response signal features' marginal distributions. Furthermore, using the joint EEG-fMRI feature distribution, we provide novel evidence for a highly distributed and dynamic encoding of task-relevant information in the human brain.

  19. Desperately seeking donors: the 'saviour sibling' decision in Quintavalle v Human Fertilisation and Embryology Authority (UK).

    Science.gov (United States)

    Hocking, Barbara Ann; Guy, Scott

    2005-08-01

    The recent House of Lords decision in Quintavalle v Human Fertilisation and Embryology Authority has raised difficult and complex issues regarding the extent to which embryo selection and reproductive technology can be used as a means of rectifying genetic disorders and treating critically ill children. This comment outlines the facts of Quintavalle and explores how the House of Lords approached the legal, ethical and policy issues that arose out of the Human Fertilisation and Embryology Authority's (UK) decision to allow reproductive and embryo technology to be used to produce a 'saviour sibling' whose tissue could be used to save the life of a critically ill child. Particular attention will be given to the implications of the decision in Quintavalle for Australian family and medical law and policy. As part of this focus, the comment explores the current Australian legislative and policy framework regarding the use of genetic and reproductive technology as a mechanism through which to assist critically ill siblings. It is argued that the present Australian framework would appear to impose significant limits on the medical uses of genetic technology and, in this context, would seem to reflect many of the principles that were articulated by the House of Lords in Quintavalle.

  20. Decision Making Model for Business Process Outsourcing of Enterprise Content Management

    Directory of Open Access Journals (Sweden)

    Zhuojun Yi

    2013-03-01

    Full Text Available Business process outsourcing (BPO in enterprise content management (ECM is a growing though immature market. BPO in ECM focuses on pursuing market transactions in the process of managing all types of content being used in organizations. However, inadequate sourcing decisions lead to organizational sensitive content exposure, high transaction cost, poor outsourcer performance, low flexibility. ECM BPO in general is rarely discussed in the literature and no discussion was found on decision making strategies in ECM BPO. In this paper, we present a decision making model for ECM BPO that will fill the literature gap and guide industry practitioners with ECM sourcing decision making strategies. Our proposed decision making model includes two parts. Part one is an ECM functional framework that shows what functionality component or functionality combinations can be outsourced. Part two is a decision making model that provides guidance for decision making in ECM BPO. We apply the model in two case studies, and the results indicate that the model can guide the sourcing decision making process for organizations, and determine the factors when considering sourcing alternatives in ECM.

  1. Effects of modeling decisions on cold region hydrological model performance: snow, soil and streamflow

    Science.gov (United States)

    Musselman, Keith; Clark, Martyn; Endalamaw, Abraham; Bolton, W. Robert; Nijssen, Bart; Arnold, Jeffrey

    2017-04-01

    Cold regions are characterized by intense spatial gradients in climate, vegetation and soil properties that determine the complex spatiotemporal patterns of snowpack evolution, frozen soil dynamics, catchment connectivity, and streamflow. These spatial gradients pose unique challenges for hydrological models, including: 1) how the spatial variability of the physical processes are best represented across a hierarchy of scales, and 2) what algorithms and parameter sets best describe the biophysical and hydrological processes at the spatial scale of interest. To address these topics, we apply the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to simulate hydrological processes at the Caribou - Poker Creeks Research Watershed in the Alaskan sub-arctic Boreal forest. The site is characterized by numerous gauged headwater catchments ranging in size from 5 sq. km to 106 sq. km with varying extents (3% to 53%) of discontinuous permafrost that permits a multi-scale paired watershed analysis of the hydrological impacts of frozen soils. We evaluate the effects of model decisions on the skill of SUMMA to simulate observed snow and soil dynamics, and the spatial integration of these processes as catchment streamflow. Decisions such as the number of soil layers, total soil column depth, and vertical soil discretization are shown to have profound impacts on the simulation of seasonal active layer dynamics. Decisions on the spatial organization (lateral connectivity, representation of riparian response units, and the spatial discretization of the hydrological landscape) are shown to be as important as accurate snowpack and soil process representation in the simulation of streamflow. The work serves to better inform hydrological model decisions for cold region hydrologic evaluation and to improve predictive capacity for water resource planning.

  2. Prisoner's Dilemma as a Model for Understanding Decisions.

    Science.gov (United States)

    Larsen, Janet D.

    1987-01-01

    Describes two classroom demonstrations, based on the prisoner's dilemma, which illustrate some elements of decision making. Examines how students either cooperate or take advantage of one another, and discusses the use of this activity as an introduction to various concepts in psychology and other social sciences. (GEA)

  3. Modeling Hospital Discharge and Placement Decision Making: Whither the Elderly.

    Science.gov (United States)

    Clark, William F.; Pelham, Anabel O.

    This paper examines the hospital discharge decision making process for elderly patients, based on observations of the operations of a long term care agency, the California Multipurpose Senior Services Project. The analysis is divided into four components: actors, factors, processes, and strategy critique. The first section discusses the major…

  4. Real Time Traffic Models, Decision Support for Traffic Management

    NARCIS (Netherlands)

    Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  5. Real time traffic models, decision support for traffic management

    NARCIS (Netherlands)

    Wismans, Luc Johannes Josephus; de Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various

  6. Appropriate models in decision support systems for river basin management

    NARCIS (Netherlands)

    Xu, YuePing; Booij, Martijn J.; Morell, M.; Todorovik, O.; Dimitrov, D.; Selenica, A.; Spirkovski, Z.

    2004-01-01

    In recent years, new ideas and techniques appear very quickly, like sustainability, adaptive management, Geographic Information System, Remote Sensing and participations of new stakeholders, which contribute a lot to the development of decision support systems in river basin management. However, the

  7. Decision making model and behavior of Iranian top managers

    Directory of Open Access Journals (Sweden)

    Aliakbar Farhangi

    2010-01-01

    Full Text Available Aesthetics relates to felt meaning generated from sensory perceptions, and involves subjective,tacit knowledge rooted in feeling and emotion. We believe the aesthetics of management isimportant, but little understood, aspect of organizational life. We propose that followers use theiraesthetic senses in making these assessments.In this article we try to discover the role of aesthetic in management and then try to find out thestyle of about 130 industrial and governmental top managers in Iran using some technique such asquestionnaire and interview. The personality and character of them will be recognized by some testsuch as KAI, MBIT, CPS, Cooper-Smith self-esteem, management style, machiavellism, internaland external control, behavior, attitude and their methods in problem solving and decision making,and the effect of this ability in productivity of their organization.At the end of this study we find out that they are strongly thinking, judging and intuition but half ofthem are extraversion. their personality & character, attitude, skills, professions, perception are soimportant for management and in making a decision more than Two-thirds:-If they make a decision never change it.-Use their aesthetic to judge others and events or found out the right way if it is rational and there isenough evidence.-Uses his experience and knowledge for decision but asks others to suggest a solution or solve theproblem.

  8. A Data Model for Algorithmic Multiple Criteria Decision Analysis

    NARCIS (Netherlands)

    Cailloux, O.; Tervonen, T.; Verhaegen, B.; Picalausa, F.

    2014-01-01

    Various software tools implementing multiple criteria decision analysis (MCDA) methods have appeared over the last decades. Although MCDA methods share common features, most of the implementing software have been developed independently from scratch. Majority of the tools have a proprietary storage

  9. Real time traffic models, decision support for traffic management

    NARCIS (Netherlands)

    Wismans, L.J.J.; Romph, de E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various con

  10. Real Time Traffic Models, Decision Support for Traffic Management

    NARCIS (Netherlands)

    Wismans, L.; De Romph, E.; Friso, K.; Zantema, K.

    2014-01-01

    Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various con

  11. Soil Organic Matter Mapping by Decision Tree Modeling

    Institute of Scientific and Technical Information of China (English)

    ZHOU Bin; ZHANG Xing-Gang; WANG Fan; WANG Ren-Chao

    2005-01-01

    Based on a case study of Longyou County, Zhejiang Province, the decision tree, a data mining method, was used to analyze the relationships between soil organic matter (SOM) and other environmental and satellite sensing spatial data.The decision tree associated SOM content with some extensive easily observable landscape attributes, such as landform,geology, land use, and remote sensing images, thus transforming the SOM-related information into a clear, quantitative,landscape factor-associated regular system. This system could be used to predict continuous SOM spatial distribution.By analyzing factors such as elevation, geological unit, soil type, land use, remotely sensed data, upslope contributing area, slope, aspect, planform curvature, and profile curvature, the decision tree could predict distribution of soil organic matter levels. Among these factors, elevation, land use, aspect, soil type, the first principle component of bitemporal Landsat TM, and upslope contributing area were considered the most important variables for predicting SOM. Results of the prediction between SOM content and landscape types sorted by the decision tree showed a close relationship with an accuracy of 81.1%.

  12. A Data Model for Algorithmic Multiple Criteria Decision Analysis

    NARCIS (Netherlands)

    Cailloux, O.; Tervonen, T.; Verhaegen, B.; Picalausa, F.

    2014-01-01

    Various software tools implementing multiple criteria decision analysis (MCDA) methods have appeared over the last decades. Although MCDA methods share common features, most of the implementing software have been developed independently from scratch. Majority of the tools have a proprietary storage

  13. Architectural considerations for modeling cognitive-emotional decision making

    NARCIS (Netherlands)

    Lotens, W.A.; Cain, B.

    2013-01-01

    There are numerous conceptual similarities between affective and rational decision making functions despite the differences between the emotional and cognitive systems. Aspects of emotion may be considered as a concurrent stream of information processing that is coupled with explicit, rational infor

  14. The Physics of Decision Making:. Stochastic Differential Equations as Models for Neural Dynamics and Evidence Accumulation in Cortical Circuits

    Science.gov (United States)

    Holmes, Philip; Eckhoff, Philip; Wong-Lin, K. F.; Bogacz, Rafal; Zacksenhouse, Miriam; Cohen, Jonathan D.

    2010-03-01

    We describe how drift-diffusion (DD) processes - systems familiar in physics - can be used to model evidence accumulation and decision-making in two-alternative, forced choice tasks. We sketch the derivation of these stochastic differential equations from biophysically-detailed models of spiking neurons. DD processes are also continuum limits of the sequential probability ratio test and are therefore optimal in the sense that they deliver decisions of specified accuracy in the shortest possible time. This leaves open the critical balance of accuracy and speed. Using the DD model, we derive a speed-accuracy tradeoff that optimizes reward rate for a simple perceptual decision task, compare human performance with this benchmark, and discuss possible reasons for prevalent sub-optimality, focussing on the question of uncertain estimates of key parameters. We present an alternative theory of robust decisions that allows for uncertainty, and show that its predictions provide better fits to experimental data than a more prevalent account that emphasises a commitment to accuracy. The article illustrates how mathematical models can illuminate the neural basis of cognitive processes.

  15. Holistic Modeling for Human-Autonomous System Interaction

    Science.gov (United States)

    2015-01-01

    Dekker  and  Woods,  1999;   Hollnagel,  2003;   Klein ,  2000;   Klein ,  et  al.,  1989;  Lewis  and  Wharton,  1997...complexities  of  human  perception,  cognition,   emotions ,   and  decision-­‐making.  Second,  the  CHAS  model  requires

  16. A new fit-for-purpose model testing framework: Decision Crash Tests

    Science.gov (United States)

    Tolson, Bryan; Craig, James

    2016-04-01

    Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

  17. Teachers’ informed decision-making in evaluation: Corollary of ELT curriculum as a human lived experience

    Directory of Open Access Journals (Sweden)

    Álvaro Hernán Quintero Polo

    2003-01-01

    Full Text Available This article characterizes informed decision-making as one important activity of evaluation in the English Language Teaching (ELT curriculum. I emphasize on a distinction between human and technical approaches to evaluation. This emphasis is consequence of my reflection upon my and some in-service teachers’ perceptions about literature and small-scale research projects related to the area of evaluation. In this article, I also intend to contribute to an understanding of why educational processes need to be seen as a lived experience for which informed decision-making can be used as a sound practice in a process of evaluation. A practical academic experience illustrates the discussions in this article. I led the practical experience as a professor of a seminar on testing and evaluation in English language teaching (ELT, in the Master’s Program in Applied Linguistics to the Teaching of English as a Foreign Language at the Distrital University in Bogotá, Colombia.

  18. Human Thermal Model Evaluation Using the JSC Human Thermal Database

    Science.gov (United States)

    Bue, Grant; Makinen, Janice; Cognata, Thomas

    2012-01-01

    Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested space environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality. The human thermal database developed at the Johnson Space Center (JSC) is intended to evaluate a set of widely used human thermal models. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models.

  19. An engineering approach to modelling, decision support and control for sustainable systems.

    Science.gov (United States)

    Day, W; Audsley, E; Frost, A R

    2008-02-12

    Engineering research and development contributes to the advance of sustainable agriculture both through innovative methods to manage and control processes, and through quantitative understanding of the operation of practical agricultural systems using decision models. This paper describes how an engineering approach, drawing on mathematical models of systems and processes, contributes new methods that support decision making at all levels from strategy and planning to tactics and real-time control. The ability to describe the system or process by a simple and robust mathematical model is critical, and the outputs range from guidance to policy makers on strategic decisions relating to land use, through intelligent decision support to farmers and on to real-time engineering control of specific processes. Precision in decision making leads to decreased use of inputs, less environmental emissions and enhanced profitability-all essential to sustainable systems.

  20. A neurocognitive model of the ethical decision-making process: implications for study and practice.

    Science.gov (United States)

    Reynolds, Scott J

    2006-07-01

    The field of business ethics is entrenched in a cognitive approach that portrays the ethical decision-making process as a completely deliberate and reasoned exercise. In light of growing concerns about the veracity of this approach, I build upon current knowledge of how the brain functions to present a neurocognitive model of ethical decision making. The model suggests that ethical decision making involves 2 interrelated yet functionally distinct cycles, a reflexive pattern matching cycle and a higher order conscious reasoning cycle, and thereby describes not only reasoned analysis, but also the intuitive and retrospective aspects of ethical decision making. The model sparks research in new areas, holds significant implications for the study of ethical decision making, and provides suggestions for improving ethical behavior in organizations.