8th KES International Conference on Intelligent Decision Technologies

CERN Document Server

Caballero, Alfonso; Howlett, Robert; Jain, Lakhmi

2016-01-01

The KES-IDT-2016 proceedings give an excellent insight into recent research, both theoretical and applied, in the field of intelligent decision making. The range of topics explored is wide, and covers methods of grouping, classification, prediction, decision support, modelling and many more in such areas as finance, linguistics, medicine, management and transportation. This proceedings contain several sections devoted to specific topics, such as: · Specialized Decision Techniques for Data Mining, Transportation and Project Management · Pattern Recognition for Decision Making Systems · New Advances of Soft Computing in Industrial and Management Engineering · Recent Advances in Fuzzy Systems · Intelligent Data Analysis and Applications · Reasoning-based Intelligent Systems · Intelligent Methods for Eye Movement Data Processing and Analysis · Intelligent Decision Technologies for Water Resources Management · Intelligent Decision Making for Uncertain Unstructured Big Data · Decision Making Theory for Ec...

Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

Directory of Open Access Journals (Sweden)

Moteaal Asadi Shirzi

2007-03-01

Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

Computational Intelligence and Decision Making Trends and Applications

CERN Document Server

Madureira, Ana; Marques, Viriato

2013-01-01

This book provides a general overview and original analysis of new developments and applications in several areas of Computational Intelligence and Information Systems. Computational Intelligence has become an important tool for engineers to develop and analyze novel techniques to solve problems in basic sciences such as physics, chemistry, biology, engineering, environment and social sciences.   The material contained in this book addresses the foundations and applications of Artificial Intelligence and Decision Support Systems, Complex and Biological Inspired Systems, Simulation and Evolution of Real and Artificial Life Forms, Intelligent Models and Control Systems, Knowledge and Learning Technologies, Web Semantics and Ontologies, Intelligent Tutoring Systems, Intelligent Power Systems, Self-Organized and Distributed Systems, Intelligent Manufacturing Systems and Affective Computing. The contributions have all been written by international experts, who provide current views on the topics discussed and pr...

Emotional Intelligence and risk taking in investment decision-making

OpenAIRE

Enrico Rubaltelli; Sergio Agnoli; Michela Rancan; Tiziana Pozzoli

2015-01-01

Previous work on investment decision-making suggested that emotions prevent investors from taking risks and from investing in a rational way, whereas other work found that there is great variability in people’s ability to manage and use emotional feedbacks. We hypothesized that people with high trait emotional intelligence should be more willing, than people with low trait emotional intelligence, to accept risks when making an investment. Data supported a model in which trait emotional intell...

Intelligent Decision-Making System with Green Pervasive Computing for Renewable Energy Business in Electricity Markets on Smart Grid

Directory of Open Access Journals (Sweden)

Park JongHyuk

2009-01-01

Full Text Available This paper is about the intelligent decision-making system for the smart grid based electricity market which requires distributed decision making on the competitive environments composed of many players and components. It is very important to consider the renewable energy and emission problem which are expected to be monitored by wireless communication networks. It is very difficult to predict renewable energy outputs and emission prices over time horizon, so it could be helpful to catch up those data on real time basis using many different kinds of communication infrastructures. On this backgrounds this paper provides an algorithm to make an optimal decision considering above factors.

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Computational intelligence for decision support in cyber-physical systems

CERN Document Server

Ali, A; Riaz, Zahid

2014-01-01

This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other. The joint dynamics of such systems result in a complex combination of computers, software, networks and physical processes all combined to establish a process flow at system level. This volume provides the audience with an in-depth vision about how to ensure dependability, safety, security and efficiency in real time by making use of computational intelligence in various CPS applications ranging from the nano-world to large scale wide area systems of systems. Key application areas include healthcare, transportation, energy, process control and robotics where intelligent decision support has key significance in establishing dynamic, ever-changing and high confidence future technologies. A recommended text for graduate students and researche...

Handbook on Decision Making Vol 2 Risk Management in Decision Making

CERN Document Server

Lu, Jie; Zhang, Guangquan

2012-01-01

This book presents innovative theories, methodologies, and techniques in the field of risk management and decision making. It introduces new research developments and provides a comprehensive image of their potential applications to readers interested in the area. The collection includes: computational intelligence applications in decision making, multi-criteria decision making under risk, risk modelling,forecasting and evaluation, public security and community safety, risk management in supply chain and other business decision making, political risk management and disaster response systems. The book is directed to academic and applied researchers working on risk management, decision making, and management information systems.

Business intelligence and financial decision-making: a theoretical approach

OpenAIRE

Mary Julieth Murillo Junco; Gustavo Cáceres Castellanos

2013-01-01

This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication ...

Business intelligence and financial decision-making: a theoretical approach

Directory of Open Access Journals (Sweden)

Mary Julieth Murillo Junco

2013-01-01

Full Text Available This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication play a role today

Leveraging business intelligence to make better decisions: Part I.

Science.gov (United States)

Reimers, Mona

2014-01-01

Data is the new currency. Business intelligence tools will provide better performing practices with a competitive intelligence advantage that will separate the high performers from the rest of the pack. Given the investments of time and money into our data systems, practice leaders must work to take every advantage and look at the datasets as a potential goldmine of business intelligence decision tools. A fresh look at decision tools created from practice data will create efficiencies and improve effectiveness for end-users and managers.

Reinforcement and Systemic Machine Learning for Decision Making

CERN Document Server

Kulkarni, Parag

2012-01-01

Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available-or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm-creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new an

Handbook on Decision Making

CERN Document Server

Jain, Lakhmi C

2010-01-01

The present "Volume 1: Techniques and Applications" of the "Handbook on Decision Making" presents a useful collection of AI techniques, as well as other complementary methodologies, that are useful for the design and development of intelligent decision support systems. Application examples of how these intelligent decision support systems can be utilized to help tackle a variety of real-world problems in different domains, such as business, management, manufacturing, transportation and food industries, and biomedicine, are presented. The handbook includes twenty condensed c

Developmental reversals in risky decision making: intelligence agents show larger decision biases than college students.

Science.gov (United States)

Reyna, Valerie F; Chick, Christina F; Corbin, Jonathan C; Hsia, Andrew N

2014-01-01

Intelligence agents make risky decisions routinely, with serious consequences for national security. Although common sense and most theories imply that experienced intelligence professionals should be less prone to irrational inconsistencies than college students, we show the opposite. Moreover, the growth of experience-based intuition predicts this developmental reversal. We presented intelligence agents, college students, and postcollege adults with 30 risky-choice problems in gain and loss frames and then compared the three groups' decisions. The agents not only exhibited larger framing biases than the students, but also were more confident in their decisions. The postcollege adults (who were selected to be similar to the students) occupied an interesting middle ground, being generally as biased as the students (sometimes more biased) but less biased than the agents. An experimental manipulation testing an explanation for these effects, derived from fuzzy-trace theory, made the students look as biased as the agents. These results show that, although framing biases are irrational (because equivalent outcomes are treated differently), they are the ironical output of cognitively advanced mechanisms of meaning making.

Transformational Leadership Style as Predictor of Decision Making Styles: Moderating Role of Emotional Intelligence

OpenAIRE

Rana Rashid Rehman; Ajmal Waheed

2012-01-01

The current study examines the relationship among transformational leadership style and decision making styles. It also determines the moderating role of emotional intelligence in predicting this relationship. Three hypotheses are generated for the study i.e., twohypotheses are to measure the relationship among transformational leadership style and decision making styles whereas third hypothesis is to assess the moderating effect of emotional intelligence. Questionnaire method is used to coll...

Operation and safety decision-making support expert system in NPP

International Nuclear Information System (INIS)

Wei Yanhui; Su Desong; Chen Weihua; Zhang Jianbo

2014-01-01

The article first reviewed three operation support systems currently used in NPP: real-time information surveillance system, important equipment surveillance system and plant process control and monitoring system, then presents the structure and function of three expert support sub-systems (intelligent alarm monitoring system, computer-based operating procedure support system, safety information expert decision support system). Finally the article discussed the meaning of a kind of operation decision making support system. (authors)

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...

Knowledge, decision making, and uncertainty

International Nuclear Information System (INIS)

Fox, J.

1986-01-01

Artificial intelligence (AI) systems depend heavily upon the ability to make decisions. Decisions require knowledge, yet there is no knowledge-based theory of decision making. To the extent that AI uses a theory of decision-making it adopts components of the traditional statistical view in which choices are made by maximizing some function of the probabilities of decision options. A knowledge-based scheme for reasoning about uncertainty is proposed, which extends the traditional framework but is compatible with it

Tools for collaborative decision-making

CERN Document Server

Zaraté, Pascale

2013-01-01

Decision-making has evolved recently thanks to the introduction of information and communication technologies in many organizations, which has led to new kinds of decision-making processes, called "collaborative decision-making", at the organizational and cognitive levels. This book looks at the development of the decision-making process in organizations. Decision-aiding and its paradigm of problem solving are defined, showing how decision-makers now need to work in a cooperative way. Definitions of cooperation and associated concepts such as collaboration and coordination are given and a framework of cooperative decision support systems is presented, including intelligent DSS, cooperative knowledge-based systems, workflow, group support systems, collaborative engineering, integrating with a collaborative decision-making model in part or being part of global projects. Several models and experimental studies are also included showing that these new processes have to be supported by new types of tools, several ...

Selected business intelligence methods for decision-making support in a finance institution

OpenAIRE

Mezera, Filip; Křupka, Jiří

2017-01-01

This article deals with decision-making support methods’ implementation in a medium size financial company with international operations. The objective of this article is to show the abilities of these methods to precise decision-making of management. At the beginning of this article there is briefly described the existing situation in this business sector in Central Europe. After that part Business Intelligence methods are described as well as the reasons while these methods have been introd...

Collaborative Decision Making in METOC

Science.gov (United States)

2002-01-01

desired effect (Eagly, & Chaiken, 1993). Arguably, artificial intelligence is representative of the best of approaches in rational decision - making ...2001), The quantum of social action and the function of emotion in decision - making , Emotional and Intelligent II: The Tangled Knot of Social...Collaborative decision making in METOC W.F. Lawless Paine College, Departments of Mathematics and Psychology Augusta, GA 30901-3182 ph: 706

The use of emotional intelligence capabilities in clinical reasoning and decision-making: A qualitative, exploratory study.

Science.gov (United States)

Hutchinson, Marie; Hurley, John; Kozlowski, Desirée; Whitehair, Leeann

2018-02-01

To explore clinical nurses' experiences of using emotional intelligence capabilities during clinical reasoning and decision-making. There has been little research exploring whether, or how, nurses employ emotional intelligence (EI) in clinical reasoning and decision-making. Qualitative phase of a larger mixed-methods study. Semistructured qualitative interviews with a purposive sample of registered nurses (n = 12) following EI training and coaching. Constructivist thematic analysis was employed to analyse the narrative transcripts. Three themes emerged: the sensibility to engage EI capabilities in clinical contexts, motivation to actively engage with emotions in clinical decision-making and incorporating emotional and technical perspectives in decision-making. Continuing to separate cognition and emotion in research, theorising and scholarship on clinical reasoning is counterproductive. Understanding more about nurses' use of EI has the potential to improve the calibre of decisions, and the safety and quality of care delivered. © 2017 John Wiley & Sons Ltd.

Making intelligent systems team players. A guide to developing intelligent monitoring systems

Science.gov (United States)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Heuristic decision model for intelligent nuclear power systems design

International Nuclear Information System (INIS)

Nassersharif, B.; Portal, M.G.; Gaeta, M.J.

1989-01-01

The objective of this project was to investigate intelligent nuclear power systems design. A theoretical model of the design process has been developed. A fundamental process in this model is the heuristic decision making for design (i.e., selection of methods, components, materials, etc.). Rule-based expert systems do not provide the completeness that is necessary to generate good design. A new method, based on the fuzzy set theory, has been developed and is presented here. A feedwater system knowledge base (KB) was developed for a prototype software experiment to benchmark the theory

Advanced intelligent computational technologies and decision support systems

CERN Document Server

Kountchev, Roumen

2014-01-01

This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

OpenAIRE

Bo Sun; Qiang Feng; Songjie Li

2012-01-01

According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

Directory of Open Access Journals (Sweden)

Bo Sun

2012-01-01

Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

The Role of Personality Traits, Core Self-Evaluation, and Emotional Intelligence in Career Decision-Making Difficulties

Science.gov (United States)

Di Fabio, Annamaria; Palazzeschi, Letizia; Bar-On, Reuven

2012-01-01

This study examines the role of personality traits, core self-evaluation, and emotional intelligence (EI) in career decision-making difficulties. Italian university students (N = 232) responded to questions on the Big Five Questionnaire, Core Self-Evaluation Scale, Bar-On Emotional Quotient Inventory, and Career Decision-Making Difficulties…

Logical Reasoning and Decision Making

OpenAIRE

Ong, D; Khaddaj, Souheil; Bashroush, Rabih

2011-01-01

Most intelligent systems have some form of \\ud decision making mechanisms built into their \\ud organisations. These normally include a logical \\ud reasoning element into their design. This paper reviews \\ud and compares the different logical reasoning strategies, \\ud and tries to address the accuracy and precision of \\ud decision making by formulating a tolerance to \\ud imprecision view which can be used in conjunction with \\ud the various reasoning strategies.

Knowledge-based dialogue in Intelligent Decision Support Systems

International Nuclear Information System (INIS)

Hollnagel, E.

1987-01-01

The overall goal for the design of Intelligent Decision Support Systems (IDSS) is to enhance understanding of the process under all operating conditions. For an IDSS to be effective, it must: select or generate the right information; produce reliable and consistent information; allow flexible and effective operator interaction; relate information presentation to current plant status and problems; and make the presentation at the right time. Several ongoing R and D programs try to design and build IDSSs. A particular example is the ESPRIT project Graphics and Knowledge Based Diaglogue for Dynamic Systems (GRADIENT). This project, the problems it addresses, and its uses, are discussed here

Decision Support System Based on Computational Collective Intelligence in Campus Information Systems

Science.gov (United States)

Saito, Yoshihito; Matsuo, Tokuro

Education institutions such as universities have a lot of information including book information, equipment administrative information, student information, and several others. The institutions also have multiple information in time series. As collective intelligence in campus, integrating and reusing these preserved information regarding career and taking a class, university can effectively support students' decision making of their getting jobs and subjects choice. Our purpose of support is to increase student's motivation. In this paper, we focus on course record and job information included in students' information, and propose the method to analyze correlation between a pattern of taking class and job lined up. Afterwards, we propose a support system regarding getting a job and taking class by using our proposed method. For a student who has his/her favorite job to get, the system supports his/her decision making of lecture choice by recommending a set of appropriate lecture groups. On another hand, for a student who does not have favorite job to get, the system supports his/her decision making of getting job by presenting appropriate job families related with lecture group in which he/she has ever taken. The contribution of this paper is showing a concrete method to reuse the campus collective information, implementing a system, and user perspectives.

Effective Approach to Elevate the Intelligence of Management Decision System

Institute of Scientific and Technical Information of China (English)

杨保安; 朱明; 唐志杰; 陈思

2003-01-01

Based on the sticking point of the low intelligence of the existing management decision system,this paper puts forward the idea of enriching and refining the knowledge of the system and endowing it with the ability to learn by means of adopting three types of heterogeneous knowledge representation and knowledge management measures.At length,this paper outlines the basic framework of an intelligence system for the sake of management decision problem.

Complementary cognitive capabilities, economic decision making, and aging.

Science.gov (United States)

Li, Ye; Baldassi, Martine; Johnson, Eric J; Weber, Elke U

2013-09-01

Fluid intelligence decreases with age, yet evidence about age declines in decision-making quality is mixed: Depending on the study, older adults make worse, equally good, or even better decisions than younger adults. We propose a potential explanation for this puzzle, namely that age differences in decision performance result from the interplay between two sets of cognitive capabilities that impact decision making, one in which older adults fare worse (i.e., fluid intelligence) and one in which they fare better (i.e., crystallized intelligence). Specifically, we hypothesized that older adults' higher levels of crystallized intelligence can provide an alternate pathway to good decisions when the fluid intelligence pathway declines. The performance of older adults relative to younger adults therefore depends on the relative importance of each type of intelligence for the decision at hand. We tested this complementary capabilities hypothesis in a broad sample of younger and older adults, collecting a battery of standard cognitive measures and measures of economically important decision-making "traits"--including temporal discounting, loss aversion, financial literacy, and debt literacy. We found that older participants performed as well as or better than younger participants on these four decision-making measures. Structural equation modeling verified our hypothesis: Older participants' greater crystallized intelligence offset their lower levels of fluid intelligence for temporal discounting, financial literacy, and debt literacy, but not for loss aversion. These results have important implications for public policy and for the design of effective decision environments for older adults.

Exploring the moderating effect of social intelligence on the relationship between entrepreneurial decision-making strategy and SME sustainable performance

Directory of Open Access Journals (Sweden)

Muhd Yusuf Dayang Hasliza

2018-01-01

Full Text Available The study reveals that causation, rather than effectuation, decision-making strategy is a more significant predictor of sustainable performance of SMEs. However, social intelligence was not found to be a significant moderator of entrepreneurial decision-making-sustainable performance relationship. The study uses data from a survey among 91 technology-based SMEs (TBS in Malaysia and employs structural equation modelling techniques for data analysis. A new instrument to measure all three variables of entrepreneurial decision-making strategy, social intelligence, and venture performance is proposed based on adoption and adaptation of existing validated scales available in literature.

Complementary Cognitive Capabilities, Economic Decision-Making, and Aging

Science.gov (United States)

Li, Ye; Baldassi, Martine; Johnson, Eric J.; Weber, Elke U.

2014-01-01

Fluid intelligence decreases with age, yet evidence about age declines in decision-making quality is mixed: Depending on the study, older adults make worse, equally good, or even better decisions than younger adults. We propose a potential explanation for this puzzle, namely that age differences in decision performance result from the interplay between two sets of cognitive capabilities that impact decision making, one in which older adults fare worse (i.e., fluid intelligence) and one in which they fare better (i.e., crystallized intelligence). Specifically, we hypothesized that older adults’ higher levels of crystallized intelligence can provide an alternate pathway to good decisions when the fluid intelligence pathway declines. The performance of older adults relative to younger adults therefore depends on the relative importance of each type of intelligence for the decision at hand. We tested this complementary capabilities hypothesis in a broad sample of younger and older adults, collecting a battery of standard cognitive measures and measures of economically important decision-making “traits”—including temporal discounting, loss aversion, financial literacy, and debt literacy. We found that older participants performed as well as or better than younger participants on these four decision-making measures. Structural equation modeling verified our hypothesis: Older participants’ greater crystallized intelligence offset their lower levels of fluid intelligence for temporal discounting, financial literacy, and debt literacy, but not for loss aversion. These results have important implications for public policy and for the design of effective decision environments for older adults. PMID:24040999

Intelligent systems

CERN Document Server

Irwin, J David

2011-01-01

Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

Artificial Intelligence at Advanced Information and Decision Systems

OpenAIRE

McCune, Brian P.

1981-01-01

Advanced Information and Decision Systems (AI-DS) is a relatively new, employee-owned company that does basic and applied research, product development, and consulting in the fields of artificial intelligence, computer science, decision analysis, operations research, control theory, estimation theory, and signal processing. AI&DS performs studies, analyses, systems design and evaluation, and software development for a variety of industrial clients and government agencies, including the Depart...

BUSINESS INTELLIGENCE TOOLS FOR DATA ANALYSIS AND DECISION MAKING

Directory of Open Access Journals (Sweden)

DEJAN ZDRAVESKI

2011-04-01

Full Text Available Every business is dynamic in nature and is affected by various external and internal factors. These factors include external market conditions, competitors, internal restructuring and re-alignment, operational optimization and paradigm shifts in the business itself. New regulations and restrictions, in combination with the above factors, contribute to the constant evolutionary nature of compelling, business-critical information; the kind of information that an organization needs to sustain and thrive. Business intelligence (“BI” is broad term that encapsulates the process of gathering information pertaining to a business and the market it functions in. This information when collated and analyzed in the right manner, can provide vital insights into the business and can be a tool to improve efficiency, reduce costs, reduce time lags and bring many positive changes. A business intelligence application helps to achieve precisely that. Successful organizations maximize the use of their data assets through business intelligence technology. The first data warehousing and decision support tools introduced companies to the power and benefits of accessing and analyzing their corporate data. Business users at every level found new, more sophisticated ways to analyze and report on the information mined from their vast data warehouses.Choosing a Business Intelligence offering is an important decision for an enterprise, one that will have a significant impact throughout the enterprise. The choice of a BI offering will affect people up and down the chain of command (senior management, analysts, and line managers and across functional areas (sales, finance, and operations. It will affect business users, application developers, and IT professionals. BI applications include the activities of decision support systems (DSS, query and reporting, online analyticalprocessing (OLAP, statistical analysis, forecasting, and data mining. Another way of phrasing this is

MOIDSS?- Mobile Online Intelligent Decision Support System, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — GRID has had a successfully completed Phase I 'Mobile Online Intelligent Decision Support System' (MOIDSS). The system developed into a total solution that supports...

Developing Information Systems for Competitive Intelligence Support.

Science.gov (United States)

Hohhof, Bonnie

1994-01-01

Discusses issues connected with developing information systems for competitive intelligence support; defines the elements of an effective competitive information system; and summarizes issues affecting system design and implementation. Highlights include intelligence information; information needs; information sources; decision making; and…

A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

Science.gov (United States)

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

Science.gov (United States)

Liao, Pei-Hung; Hsu, Pei-Ti; Chu, William; Chu, Woei-Chyn

2015-06-01

This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics. © The Author(s) 2013.

Intelligent Information Systems Institute

National Research Council Canada - National Science Library

Gomes, Carla

2004-01-01

...) at Cornell during the first three years of operation. IISI's mandate is threefold: To perform and stimulate research in computational and data-intensive methods for intelligent decision making systems...

Applications of Bayesian decision theory to intelligent tutoring systems

NARCIS (Netherlands)

Vos, Hendrik J.

1994-01-01

Some applications of Bayesian decision theory to intelligent tutoring systems are considered. How the problem of adapting the appropriate amount of instruction to the changing nature of a student's capabilities during the learning process can be situated in the general framework of Bayesian decision

BUSINESS INTELLIGENCE IN DECISION MAKING ON THE LABOR MARKET OF THE REPUBLIC OF MOLDOVA

Directory of Open Access Journals (Sweden)

Galina GLOBA

2013-12-01

Full Text Available Implementation of the business intelligence concept is enabling new opportunities for the labor market research and management. Labor market intelligence means a competent decision making process in the labor market. Such process should be based on the comprehensive set of analytical technologies and tools. The analysis of online information available at websites of state organizations working in the labor market of the Republic of Moldova has shown that many them are still at the very beginning of the effective data using.

Complementary Cognitive Capabilities, Economic Decision-Making, and Aging

OpenAIRE

Li, Ye; Baldassi, Martine; Johnson, Eric J.; Weber, Elke U.

2013-01-01

Fluid intelligence decreases with age, yet evidence about age declines in decision-making quality is mixed: Depending on the study, older adults make worse, equally good, or even better decisions than younger adults. We propose a potential explanation for this puzzle, namely that age differences in decision performance result from the interplay between two sets of cognitive capabilities that impact decision making, one in which older adults fare worse (i.e., fluid intelligence) and one in whi...

The cycle of intellingence production as support organizacional decision making

Directory of Open Access Journals (Sweden)

Ismael Cristofer Baierle

2011-12-01

Full Text Available Many authors claim that to cope with rapid changes in social and productive environments, and especially for responding quickly to customer demands and / or users in an organization, information is needed and its management. Decision-making processes also take into account only the past experiences, and this model no longer meets the precepts of today's corporate world, considering the speed with which the market and competition are in search of improvement. Centered on the concepts of Competitive Intelligence and Artificial Intelligence, this article aims to show the importance of information processing, focusing on the processes of decision making and provide a model for their organization and storage. The findings point to the use of intelligent systems, contributing to improved decision-making process and seeking to obtain answers with high quality standards relating to market demand.

Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach

OpenAIRE

Bennett, Casey C.; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This serves two potential functions: 1) a simulation environment for expl...

Intelligent system for accident identification in NPP

International Nuclear Information System (INIS)

Hernandez, J.L.

1998-01-01

Accidental situations in NPP are great concern for operators, the facility, regulatory bodies and the environmental. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre-operational Probabilistic safety Assessment and the Thermal hydraulic Safety Analysis of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid from the combination of the artificial intelligence techniques fuzzy logic and artificial neural networks. The system works with variables from the process of the first circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

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...

Decision making in the context of business intelligence and data quality

Directory of Open Access Journals (Sweden)

L. Marshall

2009-02-01

Full Text Available delaharper@cput.ac.za Making decisions in a business intelligence (BI environment can become extremely challenging and sometimes even impossible if the data on which the decisions are based are of poor quality. It is only possible to utilise data effectively when it is accurate, up-to-date, complete and available when needed. The BI decision makers and users are in the best position to determine the quality of the data available to them. It is important to ask the right questions of them; therefore the issues of information quality in the BI environment were established through a literature study. Information-related problems may cause supplier relationships to deteriorate, reduce internal productivity and the business' confidence in IT. Ultimately it can have implications for an organisation's ability to perform and remain competitive. The purpose of this article is aimed at identifying the underlying factors that prevent information from being easily and effectively utilised and understanding how these factors can influence the decision-making process, particularly within a BI environment. An exploratory investigation was conducted at a large retail organisation in South Africa to collect empirical data from BI users through unstructured interviews. Some of the main findings indicate specific causes that impact the decisions of BI users, including accuracy, inconsistency, understandability and availability of information. Key performance measures that are directly impacted by the quality of data on decision-making include waste, availability, sales and supplier fulfilment. The time spent on investigating and resolving data quality issues has a major impact on productivity. The importance of documentation was highlighted as an important issue that requires further investigation. The initial results indicate the value of

Distributed and organized decision making under resource boundedness

International Nuclear Information System (INIS)

Sawaragi, Tetsuo

1994-01-01

The coming bottleneck to be overcome in the era of the distributed and open-architectured environment will be the establishment of the rational design and coordination of the total system where multiple decision makers, problem solvers and automated machinery components coexist interacting with each other. In such an environment, they are not achieving some absolute standard of performance with unlimited amounts of resources nor with simple algorithms, but is doing as well as possible given what resources one has. In this article, we focus on the potentials of decision theory as a tool for tackling with the limited rationality under resource boundedness. First, the bottlenecks for establishing the organized and distributed decision making are summarized, and the importance of the formalization of decision activities of intelligent agents is stressed to establish an efficient and effective cooperation by distributed and organized decision making and/or problem solving. Some of the practical systems developed based on such a principle are reviewed briefly with respect to the real-time man-machine collaboration and the cooperative computational framework for the intelligent mobile robots. (author)

Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

Science.gov (United States)

Bennett, Casey C; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

Tactical decision making under stress (TADMUS) decision support system

OpenAIRE

Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.

1996-01-01

A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes and cognitive analysis of the decision making problems faced by Navy tactical officers in a shipboard Combat Information Center. Baseline testing in high intensity, peace keeping, littoral scenarios indicated...

Decision Making Based On Management Information System and Decision Support System

Directory of Open Access Journals (Sweden)

Şükrü Ada

2015-04-01

Full Text Available Information hasbecome an essentialresource for managing modern organizations. This is so because today’sbusiness environment is volatile, dynamic, turbulent and necessitates the burgeoning demand for accurate, relevant, complete,timely and economical information needed to drive the decision-making process in order to accentuate organizational abilities to manage opportunities and threat. MIS work on online mode with an average processing speed. Generally, it is used by low level management. Decision support system are powerful tool that assist corporate executives, administrators and other senior officials in making decision regarding the problem. Management Information Systems is a useful tool that provided organized and summarized information in a proper time to decision makers and enable making accurate decision for managers in organizations. This paper will discuss the concept, characteristics, types of MIS, the MIS model, and in particular it will highlight the impact and role of MIS on decision making.

Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey

Directory of Open Access Journals (Sweden)

Lefeng Cheng

2018-04-01

Full Text Available Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA, including expert system (EPS, artificial neural network (ANN, fuzzy theory, rough sets theory (RST, grey system theory (GST, swarm intelligence (SI algorithms, data mining technology, machine learning (ML, and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as

Beyond IQ: A Latent State-Trait Analysis of General Intelligence, Dynamic Decision Making, and Implicit Learning

Science.gov (United States)

Danner, Daniel; Hagemann, Dirk; Schankin, Andrea; Hager, Marieke; Funke, Joachim

2011-01-01

The present study investigated cognitive performance measures beyond IQ. In particular, we investigated the psychometric properties of dynamic decision making variables and implicit learning variables and their relation with general intelligence and professional success. N = 173 employees from different companies and occupational groups completed…

The intelligent system for accident identification in NPP

International Nuclear Information System (INIS)

Hernandez, Jorge Luis.

1998-01-01

Accidental situations in NPP are of greet concern for operators, the facility, regulatory bodies and the environment. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making when initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre operational Probabilistic Safety Assessment and the Thermal hydraulic Safety Analyses of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid system from the combination of the artificial intelligence techniques: fussy logic and artificial neural networks. The system works with variables from the process of the firsts circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

A system of system lenses for leadership decision-making.

Science.gov (United States)

Cady, Phil

2016-01-01

The sheer volume and dynamics among system agents in healthcare makes decision-making a daunting task at all levels. Being clear about what leaders mean by "healthcare system" is critical in aligning system strategy and leadership decision-making. This article presents an emerging set of lenses (ideology and beliefs, rational and irrational information processing, interpersonal social dynamics, process and value creation, and context) to help frame leadership decision-making in healthcare systems. © 2015 The Canadian College of Health Leaders.

A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

Directory of Open Access Journals (Sweden)

Tinggui Chen

2013-01-01

Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

Intelligent systems: A semiotic perspective. Volume I: Theoretical semiotics

Energy Technology Data Exchange (ETDEWEB)

Albus, J.; Meystel, A.; Quintero, R.

1996-12-31

This report contains the papers from the Proceedings of the 1996 International Multidisciplinary Conference - Theoretical Semiotics. General topics covered are: semiotic in biology: biologically inspired complex systems; intelligence in constructed complex systems; intelligence of learning and evolution; fuzzy logic and the mechanisms of generalization; information representation for decision making; sematic foundations; syntactics of intelligent systems: the kind of logic available; intelligence of recognition: the semiotic tools; and multiresolutional methods.

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

Using a group decision support system to make investment prioritisation decisions

OpenAIRE

Read, Martin; Gear, Tony; Minkes, Leonard; Irving, Ann

2013-01-01

This paper is concerned with how decision making groups involved in making investment prioritisation decisions involving funding of technology and science projects may be supported by a group decision support system (GDSS). While interested in decision outcomes, the primary focus of this paper is the role of a group support system as an aid to developing shared understanding within a group. The paper develops the conceptual framework of decision-making, communication and group support, and de...

Customer Decision Support Systems: Resources for Student Decision Making

Directory of Open Access Journals (Sweden)

Cara Okleshen Peters, Ph.D.

2005-07-01

Full Text Available This paper highlights the potential of customer decision support systems (CDSS to assist students in education-related decision making. Faculty can use these resources to more effectively advise students on various elements of college life, while students can employ them to more actively participate in their own learning and improve their academic experience. This conceptual paper summarizes consumer decision support systems (CDSS concepts and presents exemplar websites students could utilize to support their education-related decision making. Finally, the authors discuss the potential benefits and drawbacks such resources engender from a student perspective and conclude with directions for future research.

Decision-making and cognitive abilities: A review of associations between Iowa Gambling Task performance, executive functions, and intelligence.

Science.gov (United States)

Toplak, Maggie E; Sorge, Geoff B; Benoit, André; West, Richard F; Stanovich, Keith E

2010-07-01

The Iowa Gambling Task (IGT) has been used to study decision-making differences in many different clinical and developmental samples. It has been suggested that IGT performance captures abilities that are separable from cognitive abilities, including executive functions and intelligence. The purpose of the current review was to examine studies that have explicitly examined the relationship between IGT performance and these cognitive abilities. We included 43 studies that reported correlational analyses with IGT performance, including measures of inhibition, working memory, and set-shifting as indices of executive functions, as well as measures of verbal, nonverbal, and full-scale IQ as indices of intelligence. Overall, only a small proportion of the studies reported a statistically significant relationship between IGT performance and these cognitive abilities. The majority of studies reported a non-significant relationship. Of the minority of studies that reported statistically significant effects, effect sizes were, at best, small to modest, and confidence intervals were large, indicating that considerable variability in performance on the IGT is not captured by current measures of executive function and intelligence. These findings highlight the separability between decision-making on the IGT and cognitive abilities, which is consistent with recent conceptualizations that differentiate rationality from intelligence. 2010 Elsevier Ltd. All rights reserved.

Intelligent systems and soft computing for nuclear science and industry

International Nuclear Information System (INIS)

Ruan, D.; D'hondt, P.; Govaerts, P.; Kerre, E.E.

1996-01-01

The second international workshop on Fuzzy Logic and Intelligent Technologies in Nuclear Science (FLINS) addresses topics related to intelligent systems and soft computing for nuclear science and industry. The proceedings contain 52 papers in different fields such as radiation protection, nuclear safety (human factors and reliability), safeguards, nuclear reactor control, production processes in the fuel cycle, dismantling, waste and disposal, decision making, and nuclear reactor control. A clear link is made between theory and applications of fuzzy logic such as neural networks, expert systems, robotics, man-machine interfaces, and decision-support techniques by using modern and advanced technologies and tools. The papers are grouped in three sections. The first section (Soft computing techniques) deals with basic tools to treat fuzzy logic, neural networks, genetic algorithms, decision-making, and software used for general soft-computing aspects. The second section (Intelligent engineering systems) includes contributions on engineering problems such as knowledge-based engineering, expert systems, process control integration, diagnosis, measurements, and interpretation by soft computing. The third section (Nuclear applications) focusses on the application of soft computing and intelligent systems in nuclear science and industry

The role of logistics information system in the business-decision process

OpenAIRE

Galicic, Vlado; Pilepic, Ljubica

2007-01-01

The development of logistics information systems that support decision-making, together with the use of business intelligence, provides assistance and support to logistics managers in the decision process, thereby impacting on the quality of business and productivity. Being better informed and having greater intelligence for decision-making can help to create new value and gain competitive advantage. Logistics business systems in a tourism destination appreciate the importance of information ...

An intelligent decision support system for management of petroleum-contaminated sites

International Nuclear Information System (INIS)

Liquang Geng; Chan, C.W.; Zhi Chen; Huang, G.H.

2001-01-01

Groundwater and soil contamination resulted from LNAPLs (light nonaqueous phase liquids) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies have been developed and implemented in the last two decades. They are classified as ex-situ and in-situ remediation techniques. One of the problems associated with ex-situ remediation is the cost of operation. In recent years, in-situ techniques have acquired popularity. However, the selection of the optimal techniques is difficult and insufficient expertise in the process may result in large inflation of expenses. This study presents an expert system (ES) for the management of petroleum contaminated sites in which a variety of artificial intelligence (AI) techniques were used to construct a support tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation. The results from some case studies indicate that the expert system can generate cost-effective remediation alternatives to assist decision-makers. (Author)

Intelligent Decision Support System for Bank Loans Risk Classification

Institute of Scientific and Technical Information of China (English)

杨保安; 马云飞; 俞莲

2001-01-01

Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

Development of the Supported Decision Making Inventory System.

Science.gov (United States)

Shogren, Karrie A; Wehmeyer, Michael L; Uyanik, Hatice; Heidrich, Megan

2017-12-01

Supported decision making has received increased attention as an alternative to guardianship and a means to enable people with intellectual and developmental disabilities to exercise their right to legal capacity. Assessments are needed that can used by people with disabilities and their systems of supports to identify and plan for needed supports to enable decision making. This article describes the steps taken to develop such an assessment tool, the Supported Decision Making Inventory System (SDMIS), and initial feedback received from self-advocates with intellectual disability. The three sections of the SDMIS (Supported Decision Making Personal Factors Inventory, Supported Decision Making Environmental Demands Inventory, and Decision Making Autonomy Inventory) are described and implications for future research, policy, and practice are discussed.

The intelligent system for accident identification in nuclear power plant

International Nuclear Information System (INIS)

Hernandez, Jorge Luis.

1998-01-01

Accidental situations in NPP are of greet concern for operators, the facility, regulatory bodies and the environment. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making when initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre operational Probabilistic Safety Assessment and the Thermal hydraulic Safety Analyses of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid system from the combination of the artificial intelligence techniques: fussy logic and artificial neural networks. The system works with variables from the process of the firsts circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

Increases in Emotional Intelligence After an Online Training Program Are Associated With Better Decision-Making on the Iowa Gambling Task.

Science.gov (United States)

Alkozei, Anna; Smith, Ryan; Demers, Lauren A; Weber, Mareen; Berryhill, Sarah M; Killgore, William D S

2018-01-01

Higher levels of emotional intelligence have been associated with better inter and intrapersonal functioning. In the present study, 59 healthy men and women were randomized into either a three-week online training program targeted to improve emotional intelligence ( n = 29), or a placebo control training program targeted to improve awareness of nonemotional aspects of the environment ( n = 30). Compared to placebo, participants in the emotional intelligence training group showed increased performance on the total emotional intelligence score of the Mayer-Salovey-Caruso Emotional Intelligence Test, a performance measure of emotional intelligence, as well as subscales of perceiving emotions and facilitating thought. Moreover, after emotional intelligence training, but not after placebo training, individuals displayed the ability to arrive at optimal performance faster (i.e., they showed a faster learning rate) during an emotion-guided decision-making task (i.e., the Iowa Gambling Task). More specifically, although both groups showed similar performance at the start of the Iowa Gambling Task from pre- to posttraining, the participants in the emotional intelligence training group learned to choose more advantageous than disadvantageous decks than those in the placebo training group by the time they reached the "hunch" period of the task (i.e., the point in the task when implicit task learning is thought to have occurred). Greater total improvements in performance on the Iowa Gambling Task from pre- to posttraining in the emotional intelligence training group were also positively correlated with pre- to posttraining changes in Mayer-Salovey-Caruso Emotional Intelligence Test scores, in particular with changes in the ability to perceive emotions. The present study provides preliminary evidence that emotional intelligence can be trained with the help of an online training program targeted at adults; it also suggests that changes in emotional intelligence, as a

Geospatial decision support systems for societal decision making

Science.gov (United States)

Bernknopf, R.L.

2005-01-01

While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the

ENABLING SMART MANUFACTURING TECHNOLOGIES FOR DECISION-MAKING SUPPORT

Science.gov (United States)

Helu, Moneer; Libes, Don; Lubell, Joshua; Lyons, Kevin; Morris, KC

2017-01-01

Smart manufacturing combines advanced manufacturing capabilities and digital technologies throughout the product lifecycle. These technologies can provide decision-making support to manufacturers through improved monitoring, analysis, modeling, and simulation that generate more and better intelligence about manufacturing systems. However, challenges and barriers have impeded the adoption of smart manufacturing technologies. To begin to address this need, this paper defines requirements for data-driven decision making in manufacturing based on a generalized description of decision making. Using these requirements, we then focus on identifying key barriers that prevent the development and use of data-driven decision making in industry as well as examples of technologies and standards that have the potential to overcome these barriers. The goal of this research is to promote a common understanding among the manufacturing community that can enable standardization efforts and innovation needed to continue adoption and use of smart manufacturing technologies. PMID:28649678

Artificial intelligence tools decision support systems in condition monitoring and diagnosis

CERN Document Server

Galar Pascual, Diego

2015-01-01

Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource: Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniques Considers the merits of each technique as well as the issues associated with real-life application Covers classification methods, from neural networks to Bayesian and support vector machines Proposes fuzzy logic to explain the uncertainties associated with diagnostic processes Provides data sets, sample signals, and MATLAB® code for algorithm testing Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis delivers a thorough evaluation of the latest AI tools for CM, describing the most common fault diagnosis techniques used and the data acquired when these techniques are applied.

Decision-making of selectable process plans based on petri net with manufacturing constraints

DEFF Research Database (Denmark)

Xiao, Weiyue; Jones, Richard William; Yu, Fei

2016-01-01

Intelligent Computer-Aided process planning and decision making for manufacturing systems is a critical subject, that some might argue, has not received the attention it should have from the research community. Despite the progress made in the area of artificial intelligence, there has not been a...

Intelligent Aircraft Damage Assessment, Trajectory Planning, and Decision-Making under Uncertainty

Science.gov (United States)

Lopez, Israel; Sarigul-Klijn, Nesrin

Situational awareness and learning are necessary to identify and select the optimal set of mutually non-exclusive hypothesis in order to maximize mission performance and adapt system behavior accordingly. This paper presents a hierarchical and decentralized approach for integrated damage assessment and trajectory planning in aircraft with uncertain navigational decision-making. Aircraft navigation can be safely accomplished by properly addressing the following: decision-making, obstacle perception, aircraft state estimation, and aircraft control. When in-flight failures or damage occur, rapid and precise decision-making under imprecise information is required in order to regain and maintain control of the aircraft. To achieve planned aircraft trajectory and complete safe landing, the uncertainties in system dynamics of the damaged aircraft need to be learned and incorporated at the level of motion planning. The damaged aircraft is simulated via a simplified kinematic model. The different sources and perspectives of uncertainties in the damage assessment process and post-failure trajectory planning are presented and classified. The decision-making process for an emergency motion planning and landing is developed via the Dempster-Shafer evidence theory. The objective of the trajectory planning is to arrive at a target position while maximizing the safety of the aircraft given uncertain conditions. Simulations are presented for an emergency motion planning and landing that takes into account aircraft dynamics, path complexity, distance to landing site, runway characteristics, and subjective human decision.

The need for operating guidelines and a decision making framework applicable to the discovery of non-intelligent extraterrestrial life

Science.gov (United States)

Race, Margaret S.; Randolph, Richard O.

While formal principles have been adopted for the eventuality of detecting intelligent life in our galaxy (SETI Principles), no such guidelines exist for the discovery of non-intelligent extraterrestrial life within the solar system. Current scientifically based planetary protection policies for solar system exploration address how to undertake exploration, but do not provide clear guidance on what to do if and when life is detected. Considering that martian life could be detected under several different robotic and human exploration scenarios in the coming decades, it is appropriate to anticipate how detection of non-intelligent, microbial life could impact future exploration missions and activities, especially on Mars. This paper discusses a proposed set of interim guidelines based loosely on the SETI Principles and addresses issues extending from the time of discovery through future handling and treatment of extraterrestrial life on Mars or elsewhere. Based on an analysis of both scientific and ethical considerations, there is a clear need for developing operating protocols applicable at the time of discovery and a decision making framework that anticipates future missions and activities, both robotic and human. There is growing scientific confidence that the discovery of extraterrestrial life in some form is nearly inevitable. If and when life is discovered beyond Earth, non-scientific dimensions may strongly influence decisions about the nature and scope of future missions and activities. It is appropriate to encourage international discussion and consideration of the issues prior to an event of such historical significance.

Development of intelligent supervisory control system

International Nuclear Information System (INIS)

Takizawa, Y.; Fukumoto, A.; Makino, M.; Takiguchi, S.

1994-01-01

The objective of the development of an intelligent supervisory control system for next generation plants is enhancement of the operational reliability by applying the recent outcome of artificial intelligence and computer technologies. This system consists of the supervisory control and monitoring for automatic operation, the equipment operation support for historical data management and for test scheduling, the operators' decision making support for accidental plant situations and the human-friendly interface of these support functions. The verification test results showed the validity of the functions realized by this system for the next generation control room. (author)

An approach to a constructive simplification of multiagent multicriteria decision making problems via intercriteria analysis

International Nuclear Information System (INIS)

Atanassov, Krassimir; Szmidt, Eulalia; Kacprzyk, Janusz; Atanassova, Vassia

2017-01-01

A new multiagent multicriteria decision making procedure is proposed that considerably extends the existing methods by making it possible to intelligently reduce the set of criteria to be accounted for. The method employs elements of the novel Intercriteria Analysis method. The use of new tools, notably the intuitionistic fuzzy pairs and intuitionistic fuzzy index matrices provides additional information about the problem, addressed in the decision making procedure. Key words: decision making, multiagent systems, multicriteria decision making, intercriteria analysis, intuitionistic fuzzy estimation

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...

Intelligence from Space: Using Geographical Information Systems for Competitive Intelligence

NARCIS (Netherlands)

Hendriks, P.H.J.; Vriens, D.J.

2003-01-01

The spatial element, which is omnipresent in data and information relevant to organizations, is much underused in the decision-making processes within organizations. This applies also to decision-making within the domain of Competitive Intelligence. The chapter explores how the CI function may

7th KES International Conference on Intelligent Decision Technologies

CERN Document Server

Jain, Lakhmi; Howlett, Robert

2015-01-01

This book presents the 57 papers accepted for presentation at the Seventh KES International Conference on Intelligent Decision Technologies (KES-IDT 2015), held in Sorrento, Italy, in June 2015. The conference consists of keynote talks, oral and poster presentations, invited sessions and workshops on the applications and theory of intelligent decision systems and related areas. The conference provides an opportunity for the presentation and discussion of interesting new research results, promoting knowledge transfer and the generation of new ideas. The book will be of interest to all those whose work involves the development and application of intelligent decision systems.

How customer relationship management influences making better decisions

Directory of Open Access Journals (Sweden)

Fatemeh Izadi Manesh

2013-11-01

Full Text Available Customers are the primary sources of making appropriate decisions and their feedbacks normally help us improve the quality of systems. In this paper, we present an empirical study to detect important factors influencing managers of banking industry make better decisions. The proposed study designs a questionnaire in Likert scale consists of 32 questions, distributes it among some bank managers. Cronbach alpha is calculated as 0.805. In addition, Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Approx. Chi-Square are 0.701 and 1675, respectively. Based on the results of our survey, we have derived nine factors including customers’ welfare strategy, systems integration, organizational culture assessment, corporate strategies, organizational development, intelligence data strategies, supporting strategies, resource planning as well as research and development.

Information, trust and the limits of “intelligent accountability” in investment decision making: insights from the Madoff case

OpenAIRE

Stolowy, Hervé; Baker, Richard; Jeanjean, Thomas; Messner, Martin

2011-01-01

In this paper, we use the investment fraud of Bernard Madoff to inquire into the possibilities and limits of an “intelligent accountability” in the context of financial decision making. Drawing primarily upon data related to U.S. Individual investors (interviews and letters), we investigate the role of information and trust in investment decisions. We find that trust played an important role in the Madoff case. We also find that, in face-to-face encounters with the investors, Madoff successfu...

Artificial neural networks for decision-making in urologic oncology.

Science.gov (United States)

Anagnostou, Theodore; Remzi, Mesut; Lykourinas, Michael; Djavan, Bob

2003-06-01

The authors are presenting a thorough introduction in Artificial Neural Networks (ANNs) and their contribution to modern Urologic Oncology. The article covers a description of Artificial Neural Network methodology and points out the differences of Artificial Intelligence to traditional statistic models in terms of serving patients and clinicians, in a different way than current statistical analysis. Since Artificial Intelligence is not yet fully understood by many practicing clinicians, the authors have reviewed a careful selection of articles in order to explore the clinical benefit of Artificial Intelligence applications in modern Urology questions and decision-making. The data are from real patients and reflect attempts to achieve more accurate diagnosis and prognosis, especially in prostate cancer that stands as a good example of difficult decision-making in everyday practice. Experience from current use of Artificial Intelligence is also being discussed, and the authors address future developments as well as potential problems such as medical record quality, precautions in using ANNs or resistance to system use, in an attempt to point out future demands and the need for common standards. The authors conclude that both methods should continue to be used in a complementary manner. ANNs still do not prove always better as to replace standard statistical analysis as the method of choice in interpreting medical data.

Interfacing An Intelligent Decision-Maker To A Real-Time Control System

Science.gov (United States)

Evers, D. C.; Smith, D. M.; Staros, C. J.

1984-06-01

This paper discusses some of the practical aspects of implementing expert systems in a real-time environment. There is a conflict between the needs of a process control system and the computational load imposed by intelligent decision-making software. The computation required to manage a real-time control problem is primarily concerned with routine calculations which must be executed in real time. On most current hardware, non-trivial AI software should not be forced to operate under real-time constraints. In order for the system to work efficiently, the two processes must be separated by a well-defined interface. Although the precise nature of the task separation will vary with the application, the definition of the interface will need to follow certain fundamental principles in order to provide functional separation. This interface was successfully implemented in the expert scheduling software currently running the automated chemical processing facility at Lockheed-Georgia. Potential applications of this concept in the areas of airborne avionics and robotics will be discussed.

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

Science.gov (United States)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

SAMS--a systems architecture for developing intelligent health information systems.

Science.gov (United States)

Yılmaz, Özgün; Erdur, Rıza Cenk; Türksever, Mustafa

2013-12-01

In this paper, SAMS, a novel health information system architecture for developing intelligent health information systems is proposed and also some strategies for developing such systems are discussed. The systems fulfilling this architecture will be able to store electronic health records of the patients using OWL ontologies, share patient records among different hospitals and provide physicians expertise to assist them in making decisions. The system is intelligent because it is rule-based, makes use of rule-based reasoning and has the ability to learn and evolve itself. The learning capability is provided by extracting rules from previously given decisions by the physicians and then adding the extracted rules to the system. The proposed system is novel and original in all of these aspects. As a case study, a system is implemented conforming to SAMS architecture for use by dentists in the dental domain. The use of the developed system is described with a scenario. For evaluation, the developed dental information system will be used and tried by a group of dentists. The development of this system proves the applicability of SAMS architecture. By getting decision support from a system derived from this architecture, the cognitive gap between experienced and inexperienced physicians can be compensated. Thus, patient satisfaction can be achieved, inexperienced physicians are supported in decision making and the personnel can improve their knowledge. A physician can diagnose a case, which he/she has never diagnosed before, using this system. With the help of this system, it will be possible to store general domain knowledge in this system and the personnel's need to medical guideline documents will be reduced.

ADEM - a system for recording and retrieving AECB decision-making

Energy Technology Data Exchange (ETDEWEB)

Beare, J W

1995-04-01

A concept and plan is proposed for a system to record on-going decision-making by the AECB so that the decision-making can be retrieved in the future. The system could also be used to retrieve past decision-making. (author). 4 tabs., 1 fig.

ADEM - a system for recording and retrieving AECB decision-making

International Nuclear Information System (INIS)

Beare, J.W.

1995-04-01

A concept and plan is proposed for a system to record on-going decision-making by the AECB so that the decision-making can be retrieved in the future. The system could also be used to retrieve past decision-making. (author). 4 tabs., 1 fig

Intelligent decision support systems for sustainable computing paradigms and applications

CERN Document Server

Abraham, Ajith; Siarry, Patrick; Sheng, Michael

2017-01-01

This unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms. The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be explo...

The role of emotions in clinical reasoning and decision making.

Science.gov (United States)

Marcum, James A

2013-10-01

What role, if any, should emotions play in clinical reasoning and decision making? Traditionally, emotions have been excluded from clinical reasoning and decision making, but with recent advances in cognitive neuropsychology they are now considered an important component of them. Today, cognition is thought to be a set of complex processes relying on multiple types of intelligences. The role of mathematical logic (hypothetico-deductive thinking) or verbal linguistic intelligence in cognition, for example, is well documented and accepted; however, the role of emotional intelligence has received less attention-especially because its nature and function are not well understood. In this paper, I argue for the inclusion of emotions in clinical reasoning and decision making. To that end, developments in contemporary cognitive neuropsychology are initially examined and analyzed, followed by a review of the medical literature discussing the role of emotions in clinical practice. Next, a published clinical case is reconstructed and used to illustrate the recognition and regulation of emotions played during a series of clinical consultations, which resulted in a positive medical outcome. The paper's main thesis is that emotions, particularly in terms of emotional intelligence as a practical form of intelligence, afford clinical practitioners a robust cognitive resource for providing quality medical care.

Executive Function, Identity, and Career Decision-Making in College Students

Directory of Open Access Journals (Sweden)

Marilyn Welsh

2013-10-01

Full Text Available This study examined the relationship among executive function, identity, and career decision-making as self-reported by 82 college students. Participants were administered measures of executive function, identity status, career decision-making, and an index of verbal intelligence. After controlling for intelligence, self-reported difficulties with the metacognitive component of executive function were related to lower levels of identity achievement and higher levels of moratorium and diffusion. Difficulties with behavioral regulation were associated with higher levels of moratorium and foreclosure. Hierarchical multiple regressions with backward elimination indicated that individual differences in career certainty was best explained by metacognitive control and identity achievement. In contrast, variation in career uncertainty was predicted by verbal intelligence, behavior regulation, and low and high scores on identity achievement and diffusion, respectively. These preliminary results fill a gap in the current literature on career decision-making, suggesting the importance of executive function skills to this milestone process in the lives of emerging adults.

Decision Making in Biological Systems

DEFF Research Database (Denmark)

Tian, Chengzhe

This thesis consists of five projects in three topics with a shared theme of understanding cellular decision-making processes with mathematical modeling. In the first topic, we address the possible interaction between bacterial Toxin-Antitoxin (TA) systems and stringent response alarmone guanosin...

Creating Business Intelligence from Course Management Systems

Science.gov (United States)

van Dyk, Liezl; Conradie, Pieter

2007-01-01

Purpose: This article seeks to address the interface between individual learning facilitators that use course management systems (CMS) data to support decision-making and course design and institutional infrastructure providers that are responsible for institutional business intelligence. Design/methodology/approach: The design of a data warehouse…

From Management Information Systems to Business Intelligence: The Development of Management Information Needs

Directory of Open Access Journals (Sweden)

Gėlytė Kazakevičienė

2013-09-01

Full Text Available Despite the advances in IT, information systems intended for management informing did not uniformly fulfil the increased expectations of users; this can be said mostly about complex information needs. Although some of the technologies for supporting complicated insights, like management decision support systems and technologies, experienced reduction in interest both from researchers and practitioners, this did not reduce the importance of well-supported business informing and decision making. Being attributed to the group of intelligent systems and technologies, decision support (DS technologies have been largely supplemented by business intelligence (BI technologies. Both types of technologies are supported by respective information technologies, which often appear to be quite closely related. The objective of this paper is to define relations between simple and complex informing intended to satisfy different sets of needs and provided by different sets of support tools. The paper attempts to put together decision support and business intelligence technologies, based on common goals of sense-making and use of advanced analytical tools. A model of two interconnected cycles has been developed to relate the activities of decision support and business intelligence. Empirical data from earlier research is used to direct possible further insights into this area.

Decision-making conflict and the neural efficiency hypothesis of intelligence: a functional near-infrared spectroscopy investigation.

Science.gov (United States)

Di Domenico, Stefano I; Rodrigo, Achala H; Ayaz, Hasan; Fournier, Marc A; Ruocco, Anthony C

2015-04-01

Research on the neural efficiency hypothesis of intelligence (NEH) has revealed that the brains of more intelligent individuals consume less energy when performing easy cognitive tasks but more energy when engaged in difficult mental operations. However, previous studies testing the NEH have relied on cognitive tasks that closely resemble psychometric tests of intelligence, potentially confounding efficiency during intelligence-test performance with neural efficiency per se. The present study sought to provide a novel test of the NEH by examining patterns of prefrontal activity while participants completed an experimental paradigm that is qualitatively distinct from the contents of psychometric tests of intelligence. Specifically, participants completed a personal decision-making task (e.g., which occupation would you prefer, dancer or chemist?) in which they made a series of forced choices according to their subjective preferences. The degree of decisional conflict (i.e., choice difficulty) between the available response options was manipulated on the basis of participants' unique preference ratings for the target stimuli, which were obtained prior to scanning. Evoked oxygenation of the prefrontal cortex was measured using 16-channel continuous-wave functional near-infrared spectroscopy. Consistent with the NEH, intelligence predicted decreased activation of the right inferior frontal gyrus (IFG) during low-conflict situations and increased activation of the right-IFG during high-conflict situations. This pattern of right-IFG activity among more intelligent individuals was complemented by faster reaction times in high-conflict situations. These results provide new support for the NEH and suggest that the neural efficiency of more intelligent individuals generalizes to the performance of cognitive tasks that are distinct from intelligence tests. Copyright © 2015 Elsevier Inc. All rights reserved.

Overview of Intelligent Systems and Operations Development

Science.gov (United States)

Pallix, Joan; Dorais, Greg; Penix, John

2004-01-01

To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

Supporting the personnel reliability decision-making process with artificial intelligence

International Nuclear Information System (INIS)

Harte, D.C.

1991-01-01

Recent legislation concerning personnel security has vastly increased the responsibility and accountability of the security manager. Access authorization, fitness for duty, and personnel security access programs require decisions regarding an individual's trustworthiness and reliability based on the findings of a background investigation. While these guidelines provide significant data and are useful as a tool, limited resources are available to the adjudicator of derogatory information on what is and is not acceptable in terms of granting access to sensitive areas of nuclear plants. The reason why one individual is deemed unacceptable and the next acceptable may be questioned and cause discriminatory accusations. This paper is continuation of discussion on workforce reliability, focusing on the use of artificial intelligence to support the decisions of a security manager. With this support, the benefit of previous decisions helps ensure consistent adjudication of background investigations

An intelligent agent for optimal river-reservoir system management

Science.gov (United States)

Rieker, Jeffrey D.; Labadie, John W.

2012-09-01

A generalized software package is presented for developing an intelligent agent for stochastic optimization of complex river-reservoir system management and operations. Reinforcement learning is an approach to artificial intelligence for developing a decision-making agent that learns the best operational policies without the need for explicit probabilistic models of hydrologic system behavior. The agent learns these strategies experientially in a Markov decision process through observational interaction with the environment and simulation of the river-reservoir system using well-calibrated models. The graphical user interface for the reinforcement learning process controller includes numerous learning method options and dynamic displays for visualizing the adaptive behavior of the agent. As a case study, the generalized reinforcement learning software is applied to developing an intelligent agent for optimal management of water stored in the Truckee river-reservoir system of California and Nevada for the purpose of streamflow augmentation for water quality enhancement. The intelligent agent successfully learns long-term reservoir operational policies that specifically focus on mitigating water temperature extremes during persistent drought periods that jeopardize the survival of threatened and endangered fish species.

METHODOLOGY FOR ANALYSIS OF DECISION MAKING IN AIR NAVIGATION SYSTEM

Directory of Open Access Journals (Sweden)

Volodymyr Kharchenko

2011-03-01

Full Text Available Abstract. In the research of Air Navigation System as a complex socio-technical system the methodologyof analysis of human-operator's decision-making has been developed. The significance of individualpsychologicalfactors as well as the impact of socio-psychological factors on the professional activities of ahuman-operator during the flight situation development from normal to catastrophic were analyzed. On thebasis of the reflexive theory of bipolar choice the expected risks of decision-making by the Air NavigationSystem's operator influenced by external environment, previous experience and intentions were identified.The methods for analysis of decision-making by the human-operator of Air Navigation System usingstochastic networks have been developed.Keywords: Air Navigation System, bipolar choice, human operator, decision-making, expected risk, individualpsychologicalfactors, methodology of analysis, reflexive model, socio-psychological factors, stochastic network.

A fuzzy multi-criteria decision-making model for trigeneration system

International Nuclear Information System (INIS)

Wang Jiangjiang; Jing Youyin; Zhang Chunfa; Shi Guohua; Zhang Xutao

2008-01-01

The decision making for trigeneration systems is a compositive project and it should be evaluated and compared in a multi-criteria analysis method. This paper presents a fuzzy multi-criteria decision-making model (FMCDM) for trigeneration systems selection and evaluation. The multi-criteria decision-making methods are briefly reviewed combining the general decision-making process. Then the fuzzy set theory, weighting method and the FMCDM model are presented. Finally, several kinds of trigeneration systems, whose dynamical sources are, respectively stirling engine, gas turbine, gas engine and solid oxide fuel cell, are compared and evaluated with a separate generation system. The case for selecting the optimal trigeneration system applied to a residential building is assessed from the technical, economical, environmental and social aspects, and the FMCDM model combining analytic hierarchical process is applied to the trigeneration case to demonstrate the decision-making process and effectiveness of proposed model. The results show that the gas engine plus lithium bromide absorption water heater/chiller unit for the residential building is the best scheme in the five options

Multicriterial Methods used in Expert Systems for Business Decision Making

Directory of Open Access Journals (Sweden)

Cornelia MUNTEAN

2010-01-01

Full Text Available Many organizations are in front of most competitive economic environments, where, in order to survive, they must reduce costs all the time and adopt the most intelligent business strategies. In most decision making activities the manager has to decide which variant is the most advantageous, taking into account a multitude of criterions. Expert systems use the expert's knowledge and problem solving skills in a particular subject area throughout an organization, and can propose the optimal variant to be chosen. In this paper we have outlined the role of multicriterial methods in programming expert systems to decide in favor of the most eligible variant between a multitude of possibilities. We also made a case study and designed the prototype of an expert system for choosing the most profitable offer among many, in the prenegotiation stage, for a company, in order to organize the negotiation processes accor-dingly. In this respect, we tried to highlight the usefulness of multicriterial mathematical me-thods in three negotiation processes of a Romanian negotiation team with foreign negotiation teams for the acquisition of an equipment.

Neural systems analysis of decision making during goal-directed navigation.

Science.gov (United States)

Penner, Marsha R; Mizumori, Sheri J Y

2012-01-01

The ability to make adaptive decisions during goal-directed navigation is a fundamental and highly evolved behavior that requires continual coordination of perceptions, learning and memory processes, and the planning of behaviors. Here, a neurobiological account for such coordination is provided by integrating current literatures on spatial context analysis and decision-making. This integration includes discussions of our current understanding of the role of the hippocampal system in experience-dependent navigation, how hippocampal information comes to impact midbrain and striatal decision making systems, and finally the role of the striatum in the implementation of behaviors based on recent decisions. These discussions extend across cellular to neural systems levels of analysis. Not only are key findings described, but also fundamental organizing principles within and across neural systems, as well as between neural systems functions and behavior, are emphasized. It is suggested that studying decision making during goal-directed navigation is a powerful model for studying interactive brain systems and their mediation of complex behaviors. Copyright © 2011. Published by Elsevier Ltd.

A canonical theory of dynamic decision-making

Directory of Open Access Journals (Sweden)

John eFox

2013-04-01

Full Text Available Decision-making behaviour is studied in many very different fields, from medicine and economics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI and other technical disciplines. However the conceptualisation of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision making with respect to other high-level cognitive capabilities like problem-solving, planning and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuro-psychology, artificial intelligence, and decision engineering.

A Canonical Theory of Dynamic Decision-Making

Science.gov (United States)

Fox, John; Cooper, Richard P.; Glasspool, David W.

2012-01-01

Decision-making behavior is studied in many very different fields, from medicine and economics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptualization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering. PMID:23565100

Enhanced situation awareness and decision making for an intelligent reconfigurable reactor power controller

International Nuclear Information System (INIS)

Kenney, S.J.; Edwards, R.M.

1996-01-01

A Learning Automata based intelligent reconfigurable controller has been adapted for use as a reactor power controller to achieve improved reactor temperature performance. The intelligent reconfigurable controller is capable of enforcing either a classical or an optimal reactor power controller based on control performance feedback. Four control performance evaluation measures: dynamically estimated average quadratic temperature error, power, rod reactivity and rod reactivity rate were developed to provide feedback to the control decision component of the intelligent reconfigurable controller. Fuzzy Logic and Neural Network controllers have been studied for inclusion in the bank of controllers that form the intermediate level of an enhanced intelligent reconfigurable reactor power controller (IRRPC). The increased number of alternatives available to the supervisory level of the IRRPC requires enhanced situation awareness. Additional performance measures have been designed and a method for synthesizing them into a single indication of the overall performance of the currently enforced reactor power controller has been conceptualized. Modification of the reward/penalty scheme implemented in the existing IRRPC to increase the quality of the supervisory level decision process has been studied. The logogen model of human memory (Morton, 1969) and individual controller design information could be used to allocate reward to the most appropriate controller. Methods for allocating supervisory level attention were also studied with the goal of maximizing learning rate

Decision Support Systems and the Conflict Model of Decision Making: A Stimulus for New Computer-Assisted Careers Guidance Systems.

Science.gov (United States)

Ballantine, R. Malcolm

Decision Support Systems (DSSs) are computer-based decision aids to use when making decisions which are partially amenable to rational decision-making procedures but contain elements where intuitive judgment is an essential component. In such situations, DSSs are used to improve the quality of decision-making. The DSS approach is based on Simon's…

Advances in intelligent analysis of medical data and decision support systems

CERN Document Server

Iantovics, Barna

2013-01-01

This volume is a result of the fruitful and vivid discussions during the MedDecSup'2012 International Workshop bringing together a relevant body of knowledge, and new developments in the increasingly important field of medical informatics. This carefully edited book presents new ideas aimed at the development of intelligent processing of various kinds of medical information and the perfection of the contemporary computer systems for medical decision support. The book presents advances of the medical information systems for intelligent archiving, processing, analysis and search-by-content which will improve the quality of the medical services for every patient and of the global healthcare system. The book combines in a synergistic way theoretical developments with the practicability of the approaches developed and presents the last developments and achievements in  medical informatics to a broad range of readers: engineers, mathematicians, physicians, and PhD students.

Establishment and application of Competitive Intelligence System in Mobile Devices

Directory of Open Access Journals (Sweden)

Anass El Haddadi

2011-12-01

Full Text Available The strategy concept has changed dramatically: from a long range planning to strategic planning then to strategic responsiveness. This response implies moving from a concept of change to a concept of continuous evolution. In our context, the competitive intelligence system presented aims to improve decision‐making in all aspects of business life, particularly for offensive and innovative decisions. In the paper we present XPlor EveryWhere, our competitive intelligence system based on a multidimensional analysis model for mobile devices. The objective of this system is to capture the information environment in all dimensions of a decision problem, with the exploitation of information by analyzing the evolution of their interactions

The capacity for ethical decisions: the relationship between working memory and ethical decision making.

Science.gov (United States)

Martin, April; Bagdasarov, Zhanna; Connelly, Shane

2015-04-01

Although various models of ethical decision making (EDM) have implicitly called upon constructs governed by working memory capacity (WMC), a study examining this relationship specifically has not been conducted. Using a sense making framework of EDM, we examined the relationship between WMC and various sensemaking processes contributing to EDM. Participants completed an online assessment comprised of a demographic survey, intelligence test, various EDM measures, and the Automated Operation Span task to determine WMC. Results indicated that WMC accounted for unique variance above and beyond ethics education, exposure to ethical issues, and intelligence in several sensemaking processes. Additionally, a marginally significant effect of WMC was also found with reference to EDM. Individual differences in WMC appear likely to play an important role in the ethical decision-making process, and future researchers may wish to consider their potential influences.

Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS): A conceptual framework

Science.gov (United States)

Parnell, Gregory S.; Rowell, William F.; Valusek, John R.

1987-01-01

In recent years there has been increasing interest in applying the computer based problem solving techniques of Artificial Intelligence (AI), Operations Research (OR), and Decision Support Systems (DSS) to analyze extremely complex problems. A conceptual framework is developed for successfully integrating these three techniques. First, the fields of AI, OR, and DSS are defined and the relationships among the three fields are explored. Next, a comprehensive adaptive design methodology for AI and OR modeling within the context of a DSS is described. These observations are made: (1) the solution of extremely complex knowledge problems with ill-defined, changing requirements can benefit greatly from the use of the adaptive design process, (2) the field of DSS provides the focus on the decision making process essential for tailoring solutions to these complex problems, (3) the characteristics of AI, OR, and DSS tools appears to be converging rapidly, and (4) there is a growing need for an interdisciplinary AI/OR/DSS education.

The role of information systems in management decision making-an theoretical approach

Directory of Open Access Journals (Sweden)

PhD. Associate Professor Department of Management & Informatics Mihane Berisha-Namani

2010-12-01

Full Text Available In modern conditions of globalisation and development of information technology, information processing activities have come to be seen as essential to successful of businesses and organizations. Information has become essential to make decisions and crucial asset in organisations, whereas information systems is technology required for information processing. The application of information systems technology in business and organisations has opened up new possibilities for running and managing organisations, as well as has improved management decision making. The purpose of this paper is to give an understanding of the role that information systems have in management decision making and to discuss the possibilities how managers of organisations can make best use of information systems. The paper starts with identifying the functions of management and managerial roles and continue with information systems usage in three levels of decision making. It specifically addresses the way how information systems can help managers reduce uncertainty in decision making and includes some important implications of information systems usage for managers. Thus, this study provide a framework of effective use of information systems generally and offers an alternative approach to investigate the impact that information systems technology have in management decision making specifically

Tactical and strategic decision-making aids for nuclear power plant emergency response

International Nuclear Information System (INIS)

Cain, D.G.

1987-01-01

This paper examines the prospective role of computer-based decision aids for nuclear power plant emergency response. The role of these systems is subordinate to human activities, but in a complementary manner these systems process decision logic more accurately and foster a more thorough understanding of emergency situations than might other wise be possible. Within this context two decision support systems being developed are discussed. Both of these systems utilize technology derived from artificial intelligence, focussing on two different facets of emergency response. An automated emergency operating procedures (EOP) tracking expert system is described as a tactical aid for control room operator response. A reactor emergency action level monitor (REALM) expert system is proposed as a strategic decision aid for site emergency response. The discrimination between tactical and strategic decision-making is an intrinsic part of this examination

SART: an intelligent assistant system for subway control

Directory of Open Access Journals (Sweden)

P. Brézillon

2000-12-01

Full Text Available One of the main characteristics of a subway line is its large transport capacity (e.g., about 60000 travelers per hour in the Parisian subway combined with a regular transport supply. The regularity is particularly important at rush time - peak hours - when an incident can provoke important delays. Experience shows that the consequences of an incident are highly dependent on the context in which the incident occurs (e.g., peak hours or not. The decisions taken by the operators are heavily relied on the incident context, and operators often make different decisions for the same incident in different contexts. The project SART (French acronym for Support system for traffic control aims at developing an intelligent decision support system able of helping the operator in making decisions to solve an incident occurring on a line. This system relies on the notion of context. Context includes information and knowledge on the situation that do not intervene directly in the incident solving, but constrain the way in which the operator will choose a strategy at each step of the incident solving. The paper describes the SART project and highlights how Artificial Intelligence (AI techniques can contributeto knowledge acquisition and knowledge representation associated with its context of use. Particularly we discuss the notion of context and show how we use this notion to solve a real-world problem.

Fuzzy multiple objective decision making methods and applications

CERN Document Server

Lai, Young-Jou

1994-01-01

In the last 25 years, the fuzzy set theory has been applied in many disciplines such as operations research, management science, control theory, artificial intelligence/expert system, etc. In this volume, methods and applications of crisp, fuzzy and possibilistic multiple objective decision making are first systematically and thoroughly reviewed and classified. This state-of-the-art survey provides readers with a capsule look into the existing methods, and their characteristics and applicability to analysis of fuzzy and possibilistic programming problems. To realize practical fuzzy modelling, it presents solutions for real-world problems including production/manufacturing, location, logistics, environment management, banking/finance, personnel, marketing, accounting, agriculture economics and data analysis. This book is a guided tour through the literature in the rapidly growing fields of operations research and decision making and includes the most up-to-date bibliographical listing of literature on the topi...

Benefits of collective intelligence: Swarm intelligent foraging, an ethnographic research

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-12-01

Full Text Available Wisdom of crowds; bees, colonies of ants, schools of fish, flocks of birds, and fireflies flashing synchronously are all examples of highly coordinated behaviors that emerge from collective, decentralized intelligence. This article is an ethnographic study of swarm intelligence foraging of swarms and the benefits derived from collective decision making. The author used using secondary data analysis to look at the benefits of swarm intelligence in decision making to achieve intended goals. Concepts like combined decision making and consensus were discussed and four principles of swarm intelligence were also discussed viz; coordination, cooperation, deliberation and collaboration. The research found out that collective decision making in swarms is the touchstone of achieving their goals. The research further recommended corporate to adopt collective intelligence for business sustainability.

Trait Emotional Intelligence Is Related to Risk Taking when Adolescents Make Deliberative Decisions

Directory of Open Access Journals (Sweden)

Angelo Panno

2016-08-01

Full Text Available Most forms of risky behavior reach their peak during adolescence. A prominent line of research is exploring the relationship between people’s emotional self-efficacy and risk taking, but little is known about this relationship in the cognitive-deliberative domain among adolescents. The main aim of the present study consists in investigating whether trait EI (Emotional Intelligence is positively related to risk taking under predominantly cognitive-deliberative conditions among adolescents. Ninety-four adolescents played the cold version of the Columbia Card Task one month following an assessment of their trait EI. Results showed that trait EI is associated with risk taking under cognitive-deliberative conditions among adolescents. Moreover, the present research showed that trait EI is related to risk taking through the decision makers’ self-motivation. These results provide novel insights into research investigating the connections between emotional intelligence, decision science and adolescence research.

Human monitoring and decision-making in man/machine systems

International Nuclear Information System (INIS)

Johannsen, G.

1979-01-01

Monitoring and decision-making together are very well characterizing the role of the human operator in highly automated systems. In this report, the analysis of human monitoring and decision-making behavior as well as its modeling are described. The goal is to present a survey. 'Classic' and optimal control theoretic monitoring models are dealt with. The relationship between attention allocation and eye movements is discussed. As an example for applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection in continuous signals and decision-making behavior of the human operator in fault diagnosis during different operation and maintenance situations are illustrated. The computer-aided decision-making is considered as a queueing problem. It is shown to what extent computer-aiding may be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. As an appendix, the report includes an English-written paper in which the possibilities of mathematical modeling of human behavior in complex man-machine systems are critically assessed. (orig.) 891 GL/orig. 892 MKO [de

Intelligent system for accident identification in NPP; Sistema inteligente para la identificacion de accidentes en centrales nucleares

Energy Technology Data Exchange (ETDEWEB)

Hernandez, J L [Centro Nacional de Seguridad Nuclear, La Habana (Cuba)

1999-12-31

Accidental situations in NPP are great concern for operators, the facility, regulatory bodies and the environmental. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre-operational Probabilistic safety Assessment and the Thermal hydraulic Safety Analysis of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid from the combination of the artificial intelligence techniques fuzzy logic and artificial neural networks. The system works with variables from the process of the first circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

13th International Conference Intelligent Autonomous Systems

CERN Document Server

Michael, Nathan; Berns, Karsten; Yamaguchi, Hiroaki

2016-01-01

This book describes the latest research accomplishments, innovations, and visions in the field of robotics as presented at the 13th International Conference on Intelligent Autonomous Systems (IAS), held in Padua in July 2014, by leading researchers, engineers, and practitioners from across the world. The contents amply confirm that robots, machines, and systems are rapidly achieving intelligence and autonomy, mastering more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision making. A wide range of research results and applications are covered, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions have been selected through a rigorous peer-review process and contain many exciting and visionary ideas that will further galvanize the research community, spurring novel research directions. The series of biennial IAS conferences ...

The gambler's fallacy is associated with weak affective decision making but strong cognitive ability.

Directory of Open Access Journals (Sweden)

Gui Xue

Full Text Available Humans demonstrate an inherent bias towards making maladaptive decisions, as shown by a phenomenon known as the gambler's fallacy (GF. The GF has been traditionally considered as a heuristic bias supported by the fast and automatic intuition system, which can be overcome by the reasoning system. The present study examined an intriguing hypothesis, based on emerging evidence from neuroscience research, that the GF might be attributed to a weak affective but strong cognitive decision making mechanism. With data from a large sample of college students, we found that individuals' use of the GF strategy was positively correlated with their general intelligence and executive function, such as working memory and conflict resolution, but negatively correlated with their affective decision making capacities, as measured by the Iowa Gambling Task. Our result provides a novel insight into the mechanisms underlying the GF, which highlights the significant role of affective mechanisms in adaptive decision-making.

Implementing a Business Intelligence System for small and medium-sized enterprises

OpenAIRE

Sang, G.; Xu, Lai; de Vrieze, Paul Ton

2016-01-01

Over the years, Business Intelligence (BI) systems have become critically important to organizations due to the increasing fast-paced competition, the vast amount of daily generated data and the complexity of how to manage collected data. Business intelligence systems empower organizations to gain insights and to understand a clearer view of their vast data, business and customers, which help to make better decisions and hence produce better results and increase profit. BI refers to a collect...

Development of an Automated Decision-Making Tool for Supervisory Control System

Energy Technology Data Exchange (ETDEWEB)

Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Muhlheim, Michael David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Flanagan, George F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kisner, Roger A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2014-09-01

This technical report was generated as a product of the Supervisory Control for Multi-Modular Small Modular Reactor (SMR) Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (AdvSMR) Research and Development Program of the US Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular AdvSMR plants. This research activity advances the state of the art by incorporating real-time, probabilistic-based decision-making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides background information on the state of the art of automated decision-making, including the description of existing methodologies. It then presents a description of a generalized decision-making framework, upon which the supervisory control decision-making algorithm is based. The probabilistic portion of automated decision-making is demonstrated through a simple hydraulic loop example.

Teaching science for public understanding: Developing decision-making abilities

Science.gov (United States)

Siegel, Marcelle A.

One of the most important challenges educators have is teaching students how to make decisions about complex issues. In this study, methods designed to enhance students' decision-making skills and attitudes were investigated. An issue-oriented science curriculum was partly replaced with activities designed by the experimenter. The first objective of the study was to examine the effects of an instructional method to increase students' use of relevant scientific evidence in their decisions. The second goal of the research was to test whether the instructional activities could promote students' beliefs that science is relevant to them, because attitudes have been shown to affect students' performance and persistence (Schommer, 1994). Third, the study was designed to determine whether the instructional activities would affect students' beliefs that their intelligence is not fixed but can grow; this question is based on Dweck and Leggett's (1988) definition of two orientations toward intelligence---entity theorists and incremental theorists (Dweck & Leggett, 1988; Dweck & Henderson, 1989). Two urban high-school classrooms participated in this study. Tenth graders examined scientific materials about current issues involving technology and society. Instructional materials on decision making were prepared for one class of students to enhance their regular issue-oriented course, Science and Sustainability. A computer program, called Convince Me (Schank, Ranney & Hoadley, 1996), provided scaffolding for making an evidence-based decision. The experimental group's activities also included pen-and-paper lessons on decision making and the effect of experience on the structure of the brain. The control class continued to engage in Science and Sustainability decision-making activities during the time the experimental class completed the treatment. The control group did not show significant improvement on decision-making tasks, and the experimental group showed marginally

RESEARCH OF MULTICRITERIAL DECISION-MAKING MODEL FOR EDUCATIONAL INFORMATION SYSTEMS

Directory of Open Access Journals (Sweden)

V. V. Serbin

2016-09-01

Full Text Available Subject of Research. Decision-making model is offered for informational and educational systems. The study of multi-criteria model is carried out taking into account knowledge, reaction and doubt. Method. The model of material proficiency by the user is based on identification of the personal characteristics when operating with the system. As a result of personal characteristics tracking in the system, an image is formed for each user that can be used for identifying his state: knowledge level, proportion of error, handwriting information, etc. During registration the user is passing an input test. Multi-criteria test results are automatically stored in the user's personal database (agent matrix and accounted for psychological comfort, formation of the next system content, management of knowledge levels, decision-making when working with the system. The proposed method gives a more clear and "transparent situational picture" for objective decision-making. Main Results. Implementation of multi-criteria decision-making model contributes to the quality of distance education. Also, the method makes it possible to reduce the probability of guessing the correct answer, thus increases the objectivity of knowledge level evaluation in diagnostic systems for management of learning process based on remote technologies. Practical Relevance. Obtained theoretical results of the work are used in training systems on the basis of multi-criteria decision models. Thus, the proposed model leads to an increase in the average score of about 0.3-0.4 points and reduces the training time in 1.5 to 2.0 times.

Confronting the risks of terrorism: making the right decisions

International Nuclear Information System (INIS)

John Garrick, B.; Hall, James E.; Kilger, Max; McDonald, John C.; O'Toole, Tara; Probst, Peter S.; Rindskopf Parker, Elizabeth; Rosenthal, Robert; Trivelpiece, Alvin W.; Van Arsdale, Lee A.; Zebroski, Edwin L.

2004-01-01

This report offers a methodology for assessing, quantitatively, the risks of terrorism. The purpose of the methodology is to support effective decision making to combat terrorism. The emphasis is on terrorist attacks that could have catastrophic consequences. The perspective taken is that in order to make the right decisions about combating terrorism, their needs to be a systematic means of assessing the likelihood of such attacks. A process of implementation of the decisions resulting from risk assessment is essential. That process includes (1) an understanding of the nature of the threat, (2) an information system linked directly to 'intelligence' on terrorism, and (3) organizational structures that can take timely, coordinated, and effective actions. There must also be sound evidence that the methodology can be successfully applied. A description of the nature of terrorism, a terrorism risk assessment methodology, information requirements to fight terrorism, and recommendations for successful implementation is what this report is about

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

OpenAIRE

Ajay Kumar Saxena; S. 0. Bhatnagar; P. K Saxena

2002-01-01

Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives p...

The Drug Reimbursement Decision-Making System in Iran.

Science.gov (United States)

Ansaripour, Amir; Uyl-de Groot, Carin A; Steenhoek, Adri; Redekop, William K

2014-05-01

Previous studies of health policies in Iran have not focused exclusively on the drug reimbursement process. The aim of this study was to describe the entire drug reimbursement process and the stakeholders, and discuss issues faced by policymakers. Review of documents describing the administrative rules and directives of stakeholders, supplemented by published statistics and interviews with experts and policymakers. Iran has a systematic process for the assessment, appraisal, and judgment of drug reimbursements. The two most important organizations in this process are the Food and Drug Organization, which considers clinical effectiveness, safety, and economic issues, and the Supreme Council of Health Insurance, which considers various criteria, including budget impact and cost-effectiveness. Ultimately, the Iranian Cabinet approves a drug and recommends its use to all health insurance organizations. Reimbursed drugs account for about 53.5% of all available drugs and 77.3% of drug expenditures. Despite its strengths, the system faces various issues, including conflicting stakeholder aims, lengthy decision-making duration, limited access to decision-making details, and rigidity in the assessment process. The Iranian drug reimbursement system uses decision-making criteria and a structured approach similar to those in other countries. Important shortcomings in the system include out-of-pocket contributions due to lengthy decision making, lack of transparency, and conflicting interests among stakeholders. Iranian policymakers should consider a number of ways to remedy these problems, such as case studies of individual drugs and closer examination of experiences in other countries. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Intelligent power system data management systems (DBMS)

Energy Technology Data Exchange (ETDEWEB)

Middleton, A.; Macdonald, E. [GE Digital Energy, Markham, ON (Canada); Schreiner, Z. [Intelligent Process Solutions GmbH, Lindau (Germany); Bizjak, J. [Elektro Ljubljana d.d., Ljubljana (Slovenia)

2010-07-01

Network owners/operators from around the world have moved from electromechanical products to intelligent electronic devices (IEDs). Most networks have a multi-generation technology mix because protection assets have a normal application lifespan of between 10 and 40 years. Associated data capture and maintenance management regimes have therefore moved from paper based into digitized media, creating a significant increase in the volume of acquired data, such that there is now a mix of paper and digitized storage. Data is rarely consolidated or used for decision making in asset management processes once testing is completed, having a major impact on overall power system reliability. This paper presented the concept of intelligent operative maintenance management, now becoming more recognized in the industry. The concept was described as the management of operational data, resulting actions and responses, wherever and by whoever they are needed, without any additional overhead. The paper discussed new techniques of testing as well as planning and operative maintenance. The practical benefits of the new system were also presented, with particular reference to central management; simplification of routine protocols; secondary testing; and reduced cost of data handling. It was concluded that the main benefit from all of the techniques discussed in this paper is that experienced expert test engineers can focus more time upon making good, critical decisions to ensure that utilities maximize their customer service and safety regimes. 13 refs., 7 figs.

Intelligent Decision Support and Big Data for Logistics and Supply Chain Management

DEFF Research Database (Denmark)

Voss, Stefan; Sebastian, Hans-Jürgen; Pahl, Julia

2017-01-01

Intelligent Decision Support and Big Data for Logistics and Supply Chain Management” features theoretical developments, real-world applications and information systems related to solving decision problems in logistics and supply chain management. Methods include optimization, heuristics, metaheur......Intelligent Decision Support and Big Data for Logistics and Supply Chain Management” features theoretical developments, real-world applications and information systems related to solving decision problems in logistics and supply chain management. Methods include optimization, heuristics......, metaheuristics and matheuristics, simulation, agent technologies, and descriptive methods. In a sense, we were and are representing the future of logistics over the years....

Intelligent Traffic Information System a Real-Time Traffic Information System on the Shiraz Bypass

Directory of Open Access Journals (Sweden)

Sodagaran Amir

2016-01-01

Full Text Available Real-time traffic information system is an Intelligent Transportation System (ITS that allows commuters to make their traveling plan better. In this regard, an intelligent and real-time traffic information system was developed based on the video detection and an image processing algorithm was applied to measure traffic-flow according to the average speed of vehicles. Then, traffic status of each pass way is broadcasted to the electronic boards installed on all decision making entrance / exit. Different levels of congestion related to the routes ahead are shown on the boards with different colors in order to assist commuters. This system was implemented on the Shiraz Dry River’s bypasses which account as vital routes to moderate traffic of city center. Experimental results are promising due to the proximity of determined traffic status by the system compared to the detection done by traffic experts. Average speed improvement is another result of using this system. This intelligent system developed and implemented in Shiraz city for the first time in Iran.s.

Multiple Systems in Decision Making: A Neurocomputational Perspective

NARCIS (Netherlands)

Frank, M.J.; Cohen, M.X.; Sanfey, A.G.

2009-01-01

Various psychological models posit the existence of two systems that contribute to decision making. The first system is bottom-up, automatic, intuitive, emotional, and implicit, while the second system is top-down, controlled, deliberative, and explicit. It has become increasingly evident that this

Complexity in organizations and environment - adaptive changes and adaptive decision-making

Directory of Open Access Journals (Sweden)

Robert Fabac

2010-07-01

Full Text Available The features of complexity are ever more present in modern organizations and in environments in which they operate, trying to survive and be as competitive as possible. In the processes of, the so-called emergence, the formal organizational structure, designed purposefully and with a plan, is going through a change due to complexity and the need for adaptation. As a result, there is a variety of new informal groups. At the same time, the intended structural changes and business process changes occur because of the perception that the leadership and senior organizational management have of the strategic situation. Managers in modern organizations often use business intelligence (BI systems when making important business decisions. These systems offer support to the decision-making by gathering and processing relevant data and information about the company performance, but also about the data on conditions in close and remote environment. A modern company is characterized by the complex adaptive system, but the environment in which it operates together with other business subjects (agents is also complex. Consequently, the requirements for appropriate or optimal decisions and successfully completed activities are hard to meet. Given that expected future events and circumstances often occur in nonlinear mechanisms, the decisions made by following the models of traditional predicting and planning are not satisfactory. This calls for new approaches to decision making and acting.

Utility systems operation: Optimisation-based decision making

International Nuclear Information System (INIS)

Velasco-Garcia, Patricia; Varbanov, Petar Sabev; Arellano-Garcia, Harvey; Wozny, Guenter

2011-01-01

Utility systems provide heat and power to industrial sites. The importance of operating these systems in an optimal way has increased significantly due to the unstable and in the long term rising prices of fossil fuels as well as the need for reducing the greenhouse gas emissions. This paper presents an analysis of the problem for supporting operator decision making under conditions of variable steam demands from the production processes on an industrial site. An optimisation model has been developed, where besides for running the utility system, also the costs associated with starting-up the operating units have been modelled. The illustrative case study shows that accounting for the shut-downs and start-ups of utility operating units can bring significant cost savings. - Highlights: → Optimisation methodology for decision making on running utility systems. → Accounting for varying steam demands. → Optimal operating specifications when a demand change occurs. → Operating costs include start-up costs of boilers and other units. → Validated on a real-life case study. Up to 20% cost savings are possible.

Conceptual framework of knowledge management for ethical decision-making support in neonatal intensive care.

Science.gov (United States)

Frize, Monique; Yang, Lan; Walker, Robin C; O'Connor, Annette M

2005-06-01

This research is built on the belief that artificial intelligence estimations need to be integrated into clinical social context to create value for health-care decisions. In sophisticated neonatal intensive care units (NICUs), decisions to continue or discontinue aggressive treatment are an integral part of clinical practice. High-quality evidence supports clinical decision-making, and a decision-aid tool based on specific outcome information for individual NICU patients will provide significant support for parents and caregivers in making difficult "ethical" treatment decisions. In our approach, information on a newborn patient's likely outcomes is integrated with the physician's interpretation and parents' perspectives into codified knowledge. Context-sensitive content adaptation delivers personalized and customized information to a variety of users, from physicians to parents. The system provides structuralized knowledge translation and exchange between all participants in the decision, facilitating collaborative decision-making that involves parents at every stage on whether to initiate, continue, limit, or terminate intensive care for their infant.

Decision Making in Complex Systems The DeciMaS Agent-based Interdisciplinary Framework Approach

CERN Document Server

Sokolova, Marina V

2012-01-01

The study of complex systems attracts the attention of many researchers in diverse fields. Complex systems are characterized by a high number of entities and a high degree of interactions. One of the most important features is that they do not involve a central organizing authority, but the various elements that make up the systems are self-organized. Moreover, some complex systems possess an emergency priority: climate change and sustainable development research, studies of public health, ecosystem habitats, epidemiology, and medicine, among others. Unfortunately, a great number of today’s overlapping approaches fail to meet the needs of decision makers when managing complex domains. Indeed, the design of complex systems often requires the integration of a number of artificial intelligence tools and techniques. The problem can be viewed in terms of goals, states, and actions, choosing the best action to move the system toward its desired state or behavior. This is why agent-based approaches are used to mod...

14th International Conference on Intelligent Autonomous Systems

CERN Document Server

Hosoda, Koh; Menegatti, Emanuele; Shimizu, Masahiro; Wang, Hesheng

2017-01-01

This book describes the latest research advances, innovations, and visions in the field of robotics as presented by leading researchers, engineers, and practitioners from around the world at the 14th International Conference on Intelligent Autonomous Systems (IAS-14), held in Shanghai, China in July 2016. The contributions amply demonstrate that robots, machines and systems are rapidly achieving intelligence and autonomy, attaining more and more capabilities such as mobility and manipulation, sensing and perception, reasoning, and decision-making. They cover a wide range of research results and applications, and particular attention is paid to the emerging role of autonomous robots and intelligent systems in industrial production, which reflects their maturity and robustness. The contributions were selected by means of a rigorous peer-review process and highlight many exciting and visionary ideas that will further galvanize the research community and spur novel research directions. The series of biennial IAS ...

An intelligent man-machine system for future nuclear power plants

International Nuclear Information System (INIS)

Takizawa, Yoji; Hattori, Yoshiaki; Itoh, Juichiro; Fukumoto, Akira

1994-01-01

The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. The validation tests in which experienced operator crews participated were carried out in 1991 and 1992. The test results show the usefulness of the support functions and the validity of the system design approach

Decision making based on optical excitation transfer via near-field interactions between quantum dots

International Nuclear Information System (INIS)

Naruse, Makoto; Nomura, Wataru; Ohtsu, Motoichi; Aono, Masashi; Sonnefraud, Yannick; Drezet, Aurélien; Huant, Serge; Kim, Song-Ju

2014-01-01

Optical near-field interactions between nanostructured matters, such as quantum dots, result in unidirectional optical excitation transfer when energy dissipation is induced. This results in versatile spatiotemporal dynamics of the optical excitation, which can be controlled by engineering the dissipation processes and exploited to realize intelligent capabilities such as solution searching and decision making. Here, we experimentally demonstrate the ability to solve a decision making problem on the basis of optical excitation transfer via near-field interactions by using colloidal quantum dots of different sizes, formed on a geometry-controlled substrate. We characterize the energy transfer behavior due to multiple control light patterns and experimentally demonstrate the ability to solve the multi-armed bandit problem. Our work makes a decisive step towards the practical design of nanophotonic systems capable of efficient decision making, one of the most important intellectual attributes of the human brain.

Decision making based on optical excitation transfer via near-field interactions between quantum dots

Energy Technology Data Exchange (ETDEWEB)

Naruse, Makoto, E-mail: naruse@nict.go.jp [Photonic Network Research Institute, National Institute of Information and Communications Technology, 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795 (Japan); Nomura, Wataru; Ohtsu, Motoichi [Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo, 2-11-16 Yayoi, Bunkyo-ku, Tokyo 113-8656 (Japan); Aono, Masashi [Earth-Life Science Institute, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguru-ku, Tokyo 152-8550 (Japan); PRESTO, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi-shi, Saitama 332-0012 (Japan); Sonnefraud, Yannick; Drezet, Aurélien; Huant, Serge [Université Grenoble Alpes, Inst. NEEL, F-38000 Grenoble (France); CNRS, Inst. NEEL, F-38042 Grenoble (France); Kim, Song-Ju [WPI Center for Materials Nanoarchitectonics, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki 305-0044 (Japan)

2014-10-21

Optical near-field interactions between nanostructured matters, such as quantum dots, result in unidirectional optical excitation transfer when energy dissipation is induced. This results in versatile spatiotemporal dynamics of the optical excitation, which can be controlled by engineering the dissipation processes and exploited to realize intelligent capabilities such as solution searching and decision making. Here, we experimentally demonstrate the ability to solve a decision making problem on the basis of optical excitation transfer via near-field interactions by using colloidal quantum dots of different sizes, formed on a geometry-controlled substrate. We characterize the energy transfer behavior due to multiple control light patterns and experimentally demonstrate the ability to solve the multi-armed bandit problem. Our work makes a decisive step towards the practical design of nanophotonic systems capable of efficient decision making, one of the most important intellectual attributes of the human brain.

The neural system of metacognition accompanying decision-making in the prefrontal cortex

Science.gov (United States)

Qiu, Lirong; Su, Jie; Ni, Yinmei; Bai, Yang; Zhang, Xuesong; Li, Xiaoli

2018-01-01

Decision-making is usually accompanied by metacognition, through which a decision maker monitors uncertainty regarding a decision and may then consequently revise the decision. These metacognitive processes can occur prior to or in the absence of feedback. However, the neural mechanisms of metacognition remain controversial. One theory proposes an independent neural system for metacognition in the prefrontal cortex (PFC); the other, that metacognitive processes coincide and overlap with the systems used for the decision-making process per se. In this study, we devised a novel “decision–redecision” paradigm to investigate the neural metacognitive processes involved in redecision as compared to the initial decision-making process. The participants underwent a perceptual decision-making task and a rule-based decision-making task during functional magnetic resonance imaging (fMRI). We found that the anterior PFC, including the dorsal anterior cingulate cortex (dACC) and lateral frontopolar cortex (lFPC), were more extensively activated after the initial decision. The dACC activity in redecision positively scaled with decision uncertainty and correlated with individual metacognitive uncertainty monitoring abilities—commonly occurring in both tasks—indicating that the dACC was specifically involved in decision uncertainty monitoring. In contrast, the lFPC activity seen in redecision processing was scaled with decision uncertainty reduction and correlated with individual accuracy changes—positively in the rule-based decision-making task and negatively in the perceptual decision-making task. Our results show that the lFPC was specifically involved in metacognitive control of decision adjustment and was subject to different control demands of the tasks. Therefore, our findings support that a separate neural system in the PFC is essentially involved in metacognition and further, that functions of the PFC in metacognition are dissociable. PMID:29684004

Information processing in decision-making systems.

Science.gov (United States)

van der Meer, Matthijs; Kurth-Nelson, Zeb; Redish, A David

2012-08-01

Decisions result from an interaction between multiple functional systems acting in parallel to process information in very different ways, each with strengths and weaknesses. In this review, the authors address three action-selection components of decision-making: The Pavlovian system releases an action from a limited repertoire of potential actions, such as approaching learned stimuli. Like the Pavlovian system, the habit system is computationally fast but, unlike the Pavlovian system permits arbitrary stimulus-action pairings. These associations are a "forward'' mechanism; when a situation is recognized, the action is released. In contrast, the deliberative system is flexible but takes time to process. The deliberative system uses knowledge of the causal structure of the world to search into the future, planning actions to maximize expected rewards. Deliberation depends on the ability to imagine future possibilities, including novel situations, and it allows decisions to be taken without having previously experienced the options. Various anatomical structures have been identified that carry out the information processing of each of these systems: hippocampus constitutes a map of the world that can be used for searching/imagining the future; dorsal striatal neurons represent situation-action associations; and ventral striatum maintains value representations for all three systems. Each system presents vulnerabilities to pathologies that can manifest as psychiatric disorders. Understanding these systems and their relation to neuroanatomy opens up a deeper way to treat the structural problems underlying various disorders.

Emotional Intelligence and School Leadership

Science.gov (United States)

Gray, David

2009-01-01

Emotional intelligence is the cornerstone of every decision a principal makes; solving problems and making judgments are part of a leader's system of values and beliefs. Mayer and Salovney (1997) described emotionally intelligent leaders as those who are able to perceive and understand emotions and to regulate emotions to foster emotional and…

Challenging problems and solutions in intelligent systems

CERN Document Server

Grzegorzewski, Przemysław; Kacprzyk, Janusz; Owsiński, Jan; Penczek, Wojciech; Zadrożny, Sławomir

2016-01-01

This volume presents recent research, challenging problems and solutions in Intelligent Systems– covering the following disciplines: artificial and computational intelligence, fuzzy logic and other non-classic logics, intelligent database systems, information retrieval, information fusion, intelligent search (engines), data mining, cluster analysis, unsupervised learning, machine learning, intelligent data analysis, (group) decision support systems, intelligent agents and multi-agent systems, knowledge-based systems, imprecision and uncertainty handling, electronic commerce, distributed systems, etc. The book defines a common ground for sometimes seemingly disparate problems and addresses them by using the paradigm of broadly perceived intelligent systems. It presents a broad panorama of a multitude of theoretical and practical problems which have been successfully dealt with using the paradigm of intelligent computing.

[Artificial intelligence] AI for protection systems

Energy Technology Data Exchange (ETDEWEB)

Aggarwal, R.; Johns, A.

1997-12-31

The reliable operation of large power systems with small stability margins is highly dependent on control systems and protection devices. Progress in the field of microprocessor systems and demanding requirements in respect of the performance of protective relays are the reasons for digital device applications to power system protection. The superiority of numeric protection over its analogue alternatives is attributed to such factors as accurate extraction of the fundamental voltage and current components through filtering, functional benefits resulting from multi-processor design and extensive self-monitoring, etc. However, all these reasons have not led to a major impact on speed, sensitivity and selectivity of primary protective relays, and the gains are only marginal; this is so because conventional digital relays still rely on deterministic signal models and a heuristic approach for decision making, so that only a fraction of the information contained within voltage and current signals as well as knowledge about the plant to be protected is used. The performance of digital relays may be substantially improved if the decision making is based on elements of artificial intelligence (AI). (Author)

Decentralised water systems: emotional influences on resource decision making.

Science.gov (United States)

Mankad, Aditi

2012-09-01

The study of emotion has gathered momentum in the field of environmental science, specifically in the context of community resource decision-making. Of particular interest in this review is the potential influence of emotion, risk and threat perception on individuals' decisions to acceptance and adopt decentralised water systems, such as rainwater tanks and greywater systems. The role of message framing is also considered in detail, as well as the influences that different types of framing can have on decision making. These factors are considered as possible predictors for analysing community acceptance of decentralised water in urban environments. Concepts believed to be influenced by emotion, such as trust and framing, are also discussed as potentially meaningful contributors to an overall model of community acceptance of decentralised water. Recommendations are made for how emotion-based concepts, such as risk and threat, can be targeted to facilitate widespread adoption of decentralised systems and how researchers can explore different types of emotions that influence decision making in distinct ways. This review is an important theoretical step in advancing the psycho-social understanding of acceptance and adoption of on-site water sources. Avenues for future research are recommended, including the need for greater theoretical development to encourage future social science research on decentralised systems. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Multiple criteria decision making for sustainable energy and transportation systems. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Ehrgott, Matthias [Auckland Univ. (New Zealand). Dept. of Engineering Science; Naujoks, Boris [Login GmbH, Schwelm (Germany).; Stewart, Theodor J. [Cape Town Univ., Rondebosch (South Africa). Dept. of Statistical Sciences; Wallenius, Jyrki (eds.) [Helsinki School of Economics (Finland). Dept. of Business Technology

2010-07-01

In the twenty-first century the sustainability of energy and transportation systems is on the top of the political agenda in many countries around the world and governments are establishing policies towards a sustainable, low emissions energy future. Environmental impacts of human economic activity necessitate the consideration of conflicting goals in decision making processes to develop sustainable systems. Any sustainable development has to reconcile conflicting economic and environmental objectives and criteria. The science of multiple criteria decision making has a lot to offer in addressing this need. Decision making with multiple (conflicting) criteria is the topic of research that is at the heart of the International Society of Multiple Criteria Decision Making. This book is based on selected papers presented at the societies 19th International Conference, held at The University of Auckland, New Zealand, from 7th to 12th January 2008 under the theme ''MCDM for Sustainable Energy and Transportation Systems''. (orig.)

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.

Decision support, analytics, and business intelligence

CERN Document Server

Power, Daniel J

2013-01-01

Competition is becoming more intense and decision makers are encountering increasing complexity, rapid change, and higher levels of risk. In many situations, the solution is more and better computerized decision support, especially analytics and business intelligence. Today managers need to learn about and understand computerized decision support. If a business is to succeed, managers must know much more about information technology solutions. This second edition of a powerful introductory book is targeted at busy managers and MBA students who need to grasp the basics of computerized decision support, including the following: What are analytics? What is a decision support system? How can managers identify opportunities to create innovative computerized support? Inside, the author addresses these questions and some 60 more fundamental questions that are key to understanding the rapidly changing realm of computerized decision support. In a short period of time, you'll "get up to speed" on decision support, anal...

Intellectual decision-making system in the context of potentially dangerous nuclear power facilities

Directory of Open Access Journals (Sweden)

Danilov Alexander

2018-01-01

Full Text Available The article deals with intelligent operation decision support system under condition of potentially hazardous nuclear facilities. The proposed system is referred to the class of advising systems and does not make final decisions in case of deviations of parameters to be analyzed, but generates general ways to solve an encountered problem and issues a set of recommendations for the plant personnel. In the article a fuzzy logic tool is used as mathematic tool. Lessons learnt from operation of nuclear facilities demonstrate that existing critical components (parts, areas, welding joints are subject to increased failure under conditions of high operational loads, including beyond design loads and negative environmental impact. Usually in that situation there is probability of equipment integrity failure, when the unit is at power, with severe defect downing. For instance, the coolant leak and potential development of initial penetration defect to critical dimensions. In other words, in fact, the final observable result is always one – formation and development of operational crack which jeopardizes design integrity of the component and, accordingly, seriously compromises the nuclear power unit operation. The proposed situational model is linked with real knowledge data base where generated situational pairs are stored. The expert system is used for knowledge data base formation. Actually the proposed system consists of two independent fuzzy systems. From mathematical tool point of view, the advantage of such systems combination is lack of defuzzification unit in the first system and fuzzification unit in the second one.

A Decision Support System for Optimum Use of Fertilizers

Energy Technology Data Exchange (ETDEWEB)

R. L. Hoskinson; J. R. Hess; R. K. Fink

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

The application of reduced-processing decision support systems to facilitate the acquisition of decision-making skills.

Science.gov (United States)

Perry, Nathan C; Wiggins, Mark W; Childs, Merilyn; Fogarty, Gerard

2013-06-01

The study was designed to examine whether the availability of reduced-processing decision support system interfaces could improve the decision making of inexperienced personnel in the context of Although research into reduced-processing decision support systems has demonstrated benefits in minimizing cognitive load, these benefits have not typically translated into direct improvements in decision accuracy because of the tendency for inexperienced personnel to focus on less-critical information. The authors investigated whether reduced-processing interfaces that direct users' attention toward the most critical cues for decision making can produce improvements in decision-making performance. Novice participants made incident command-related decisions in experimental conditions that differed according to the amount of information that was available within the interface, the level of control that they could exert over the presentation of information, and whether they had received decision training. The results revealed that despite receiving training, participants improved in decision accuracy only when they were provided with an interface that restricted information access to the most critical cues. It was concluded that an interface that restricts information access to only the most critical cues in the scenario can facilitate improvements in decision performance. Decision support system interfaces that encourage the processing of the most critical cues have the potential to improve the accuracy and timeliness of decisions made by inexperienced personnel.

Computational intelligence paradigms in economic and financial decision making

CERN Document Server

Resta, Marina

2016-01-01

The book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background.

What makes you clever the puzzle of intelligence

CERN Document Server

Partridge, Derek

2014-01-01

From Black Holes and Big Bangs to the Higgs boson and the infinitesimal building blocks of all matter, modern science has been spectacularly successful, with one glaring exception - intelligence. Intelligence still remains as one of the greatest mysteries in science. How do you chat so effortlessly? How do you remember, and why do you forget? From a basis of ten maxims What Makes You Clever explains the difficulties as well as the persuasive and persistent over-estimations of progress in Artificial Intelligence. Computers have transformed our lives, and will continue to do so for many years to come. But ever since the Turing Test proposed in 1950 up to IBM's Deep Blue computer that won the second six-game match against world champion Garry Kasparov, the science of artificial intelligence has struggled to make progress. The reader's expertise is engaged to probe human language, machine learning, neural computing, holistic systems and emergent phenomenon. What Makes You Clever reveals the difficulties that s...

Smart Building: Decision Making Architecture for Thermal Energy Management.

Science.gov (United States)

Uribe, Oscar Hernández; Martin, Juan Pablo San; Garcia-Alegre, María C; Santos, Matilde; Guinea, Domingo

2015-10-30

Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction.

Smart Building: Decision Making Architecture for Thermal Energy Management

Directory of Open Access Journals (Sweden)

Oscar Hernández Uribe

2015-10-01

Full Text Available Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction.

Green Decision Making: How Systemic Planning can support Strategic Decision Making for Sustainable Transport Development

DEFF Research Database (Denmark)

Leleur, Steen

for Strategic Management. The book was published in 2012 by Springer-Verlag, London, as a research monograph in the publisher’s series about Decision Engineering. The intention behind this new book – with its focus upon ‘greening’ of strategic decisions – is to provide a general and less technical description......The book is based on my participation in the SUSTAIN research project 2012-2017 about National Sustainable Transport Planning funded by the Danish Research Council (Innovationsfonden). Many of the issues treated here have a backdrop in my book Complex Strategic Choices – Applying Systemic Planning...... to this application area. In fact a company relocation decision case has been used to introduce the potential of SP as regards providing decision support for strategic decision making. A main concern in this presentation of SP, which deviates from the Springer book referred to above, is to highlight that ‘greening...

New trends in computational collective intelligence

CERN Document Server

Kim, Sang-Wook; Trawiński, Bogdan

2015-01-01

This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

IMPROVING THE QUALITY OF THE DECISION MAKING BY USING BUSINESS INTELLIGENCE SOLUTIONS

Directory of Open Access Journals (Sweden)

MARIA Dan Stefan

2009-05-01

Full Text Available On the basis of the decision making stands information, as one of the main elements that determine the evolution of our-days society. As a consequence, data analysis tends to become a priority in the activity of an organization for decision making. The di

Improving societal acceptance of rad waste management policy decisions: an approach based on complex intelligence

International Nuclear Information System (INIS)

Rao, Suman

2008-01-01

In today's context elaborate public participation exercises are conducted around the world to elicit and incorporate societal risk perceptions into nuclear policy Decision-Making. However, on many occasions, such as in the case of rad waste management, the society remains unconvinced about these decisions. This naturally leads to the questions: are techniques for incorporating societal risk perceptions into the rad waste policy decision making processes sufficiently mature? How could societal risk perceptions and legal normative principles be better integrated in order to render the decisions more equitable and convincing to society? Based on guidance from socio-psychological research this paper postulates that a critical factor for gaining/improving societal acceptance is the quality and adequacy of criteria for option evaluation that are used in the policy decision making. After surveying three rad waste public participation cases, the paper identifies key lacunae in criteria abstraction processes as currently practiced. A new policy decision support model CIRDA: Complex Intelligent Risk Discourse Abstraction model that is based on the heuristic of Risk-Risk Analysis is proposed to overcome these lacunae. CIRDA's functionality of rad waste policy decision making is modelled as a policy decision-making Abstract Intelligent Agent and the agent program/abstraction mappings are presented. CIRDA is then applied to a live (U.K.) rad waste management case and the advantages of this method as compared to the Value Tree Method as practiced in the GB case are demonstrated. (author)

Interactive system for decision-making in power engineering

International Nuclear Information System (INIS)

Gabrzhinskij, I.; Skurovets, V.

1988-01-01

Classification of factors, affecting decision-making in the process of power engineering management is given. General formulation of the problem and main stages of decision-making are considered. Principle scheme of heuristic procedure of decision-making is suggested

The role of emotion in clinical decision making: an integrative literature review.

Science.gov (United States)

Kozlowski, Desirée; Hutchinson, Marie; Hurley, John; Rowley, Joanne; Sutherland, Joanna

2017-12-15

Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. A systematic search of the bibliographic databases PubMed, PsychINFO, and CINAHL (EBSCO) was conducted to identify empirical studies of clinician populations. Search terms were focused to identify studies reporting clinician emotion OR clinician emotional intelligence OR emotional competence AND clinical decision making OR clinical reasoning. Twenty three papers were retained for synthesis. These represented empirical work from qualitative, quantitative, and mixed-methods approaches and comprised work with a focus on experienced emotion and on skills associated with emotional intelligence. The studies examined nurses (10), physicians (7), occupational therapists (1), physiotherapists (1), mixed clinician samples (3), and unspecified infectious disease experts (1). We identified two main themes in the context of clinical decision making: the subjective experience of emotion; and, the application of emotion and cognition in CDM. Sub-themes under the subjective experience of emotion were: emotional response to contextual pressures; emotional responses to others; and, intentional exclusion of emotion from CDM. Under the application of emotion and cognition in CDM, sub-themes were: compassionate emotional labour - responsiveness to patient emotion within CDM; interdisciplinary tension regarding the significance and meaning of emotion in CDM; and, emotion and moral judgement. Clinicians' experienced emotions can and do affect clinical decision making, although acknowledgement of that is far from universal. Importantly, this occurs in the in the absence of a

Decision-making and problem-solving methods in automation technology

Science.gov (United States)

Hankins, W. W.; Pennington, J. E.; Barker, L. K.

1983-01-01

The state of the art in the automation of decision making and problem solving is reviewed. The information upon which the report is based was derived from literature searches, visits to university and government laboratories performing basic research in the area, and a 1980 Langley Research Center sponsored conferences on the subject. It is the contention of the authors that the technology in this area is being generated by research primarily in the three disciplines of Artificial Intelligence, Control Theory, and Operations Research. Under the assumption that the state of the art in decision making and problem solving is reflected in the problems being solved, specific problems and methods of their solution are often discussed to elucidate particular aspects of the subject. Synopses of the following major topic areas comprise most of the report: (1) detection and recognition; (2) planning; and scheduling; (3) learning; (4) theorem proving; (5) distributed systems; (6) knowledge bases; (7) search; (8) heuristics; and (9) evolutionary programming.

Conceptualising a system for quality clinical decision-making in ...

African Journals Online (AJOL)

As a feedback mechanism to promote or improve the quality of clinical decisions in nursing, standards for quality clinical decision-making are proposed in an exemplary manner. In addition, a system for quality clinical decisionmaking in nursing capitalises on the heritage of the nursing process. Considering the changes and ...

Intelligent monitoring, control, and security of critical infrastructure systems

CERN Document Server

Polycarpou, Marios

2015-01-01

This book describes the challenges that critical infrastructure systems face, and presents state of the art solutions to address them. How can we design intelligent systems or intelligent agents that can make appropriate real-time decisions in the management of such large-scale, complex systems? What are the primary challenges for critical infrastructure systems? The book also provides readers with the relevant information to recognize how important infrastructures are, and their role in connection with a society’s economy, security and prosperity. It goes on to describe state-of-the-art solutions to address these points, including new methodologies and instrumentation tools (e.g. embedded software and intelligent algorithms) for transforming and optimizing target infrastructures. The book is the most comprehensive resource to date for professionals in both the private and public sectors, while also offering an essential guide for students and researchers in the areas of modeling and analysis of critical in...

The consequences of introducing IT systems for decision-making processes in healthcare institutions

Directory of Open Access Journals (Sweden)

Marzena Furtak-Niczyporuk

2017-03-01

  Aim: The aim of the study was the diagnosis of management decision-making in the therapeutic entity, for possible implementation tools in the form of an information system, which could accelerate and support the rational process of making those decisions. In addition, work was to evaluate the role of management decisions and the implications of the information system on the process of rational decision-making in the management entity therapeutic.   Material and Methods: The case study method allowed us to show the practical applications and benefits resulting from the application system to support rational decision-making management, in particular in terms of reducing costs and improving the organization of health services offered.   The results and conclusions: Presented system generates a database to support rational decision-making process in the field of management, minimize their costs while improving the organization of health services. Ability to use various functions of the system allows for multi-segment analysis, thanks to the specially chosen and condensed information, both in the form of text and graphics over any time horizon. Benefits of the implications of the system is the speed and efficiency of the whole process of treatment, as well as the reduction of administrative tasks of medical staff, which increases the time for the patient.

Neuro-Based Artificial Intelligence Model for Loan Decisions

OpenAIRE

Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

2010-01-01

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 backpr...

Warfighter decision making performance analysis as an investment priority driver

Science.gov (United States)

Thornley, David J.; Dean, David F.; Kirk, James C.

2010-04-01

Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.

[Cognitive errors in diagnostic decision making].

Science.gov (United States)

Gäbler, Martin

2017-10-01

Approximately 10-15% of our diagnostic decisions are faulty and may lead to unfavorable and dangerous outcomes, which could be avoided. These diagnostic errors are mainly caused by cognitive biases in the diagnostic reasoning process.Our medical diagnostic decision-making is based on intuitive "System 1" and analytical "System 2" diagnostic decision-making and can be deviated by unconscious cognitive biases.These deviations can be positively influenced on a systemic and an individual level. For the individual, metacognition (internal withdrawal from the decision-making process) and debiasing strategies, such as verification, falsification and rule out worst-case scenarios, can lead to improved diagnostic decisions making.

Intelligent systems in oil field development under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Pacheco, Marco A.C.; Vellasco, Marley M.B.R. (eds.) [PUC-Rio, Rio de Janeiro (Brazil). Dept. of Electrical Engineering

2009-07-01

Intelligent Systems use a range of methodologies for analysis, pre-processing, storage, organization, enhancing and mining of operational data, turning it into useful information and knowledge for decision makers in business enterprises. These intelligent technologies for decision support have been used with success by companies and organizations that are looking for competitive advantages whenever the issues on forecast, optimization, risks analysis, fraud detection, and decision under uncertainties are presented. Intelligent Systems (IS) offer to managers and decision makers the best solutions for complex applications, normally considered difficult, very restrictive or even impossible. The use of such techniques leads to a revolutionary process which has a significant impact in the business management strategy, by providing on time, correct information, ready to use. Computational intelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy as well as modern finance theories, such as real options theory, are here presented and exemplified in oil and gas exploitation and production. This book is addressed to executives and students, directly involved or interested in intelligent management in different fields. (orig.)

Implications of Decision Making Research for Decision Support and Displays

OpenAIRE

Morrison, Jeffrey G.; Kelly, Richard T.; Moore, Ronald A.; Hutchins, Susan G.

1998-01-01

To appear in J. A. Cannon-Bowers & E. Salas (Eds.), Decision Making Under Stress: Implications for Training and Simulation. A prototype decision support system (DSS) was developed to enhance Navy tactical decision making based on naturalistic decision processes. Displays were developed to support critical decision making tasks through recognition-primed and explanation-based reasoning processes, and cognitive analysis was conducted of the decision making problems faced by Navy ...

Operational and real-time Business Intelligence

Directory of Open Access Journals (Sweden)

Daniela Ioana SANDU

2008-01-01

Full Text Available A key component of a company’s IT framework is a business intelligence (BI system. BI enables business users to report on, analyze and optimize business operations to reduce costs and increase revenues. Organizations use BI for strategic and tactical decision making where the decision-making cycle may span a time period of several weeks (e.g., campaign management or months (e.g., improving customer satisfaction.Competitive pressures coming from a very dynamic business environment are forcing companies to react faster to changing business conditions and customer requirements. As a result, there is now a need to use BI to help drive and optimize business operations on a daily basis, and, in some cases, even for intraday decision making. This type of BI is usually called operational business intelligence and real-time business intelligence.

Intelligent decision technology support in practice

CERN Document Server

Neves-Silva, Rui; Jain, Lakhmi; Phillips-Wren, Gloria; Watada, Junzo; Howlett, Robert

2016-01-01

This book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications.  Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative techniq...

Dynamic vulnerability assessment and intelligent control for sustainable power systems

CERN Document Server

Gonzalez-Longatt, Francisco

2018-01-01

Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

Intelligent Structured Intermittent Auscultation (ISIA): evaluation of a decision-making framework for fetal heart monitoring of low-risk women

Science.gov (United States)

2014-01-01

Background Research-informed fetal monitoring guidelines recommend intermittent auscultation (IA) for fetal heart monitoring for low-risk women. However, the use of cardiotocography (CTG) continues to dominate many institutional maternity settings. Methods A mixed methods intervention study with before and after measurement was undertaken in one secondary level health service to facilitate the implementation of an initiative to encourage the use of IA. The intervention initiative was a decision-making framework called Intelligent Structured Intermittent Auscultation (ISIA) introduced through an education session. Results Following the intervention, medical records review revealed an increase in the use of IA during labour represented by a relative change of 12%, with improved documentation of clinical findings from assessments, and a significant reduction in the risk of receiving an admission CTG (RR 0.75, 95% CI, 0.60 – 0.95, p = 0.016). Conclusion The ISIA informed decision-making framework transformed the practice of IA and provided a mechanism for knowledge translation that enabled midwives to implement evidence-based fetal heart monitoring for low risk women. PMID:24884597

The Intelligent Technologies of Electronic Information System

Science.gov (United States)

Li, Xianyu

2017-08-01

Based upon the synopsis of system intelligence and information services, this paper puts forward the attributes and the logic structure of information service, sets forth intelligent technology framework of electronic information system, and presents a series of measures, such as optimizing business information flow, advancing data decision capability, improving information fusion precision, strengthening deep learning application and enhancing prognostic and health management, and demonstrates system operation effectiveness. This will benefit the enhancement of system intelligence.

A Decision Support System for Optimum Use of Fertilizers

Energy Technology Data Exchange (ETDEWEB)

Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend in the agricultural decision-making process.

About Problems of Decision Making in Social and Economic Systems

OpenAIRE

Voloshyn, Oleksiy

2006-01-01

The reasons of a restricted applicability of the models of decision making in social and economic systems. 3 basic principles of growth of their adequacy are proposed: "localization" of solutions, direct account of influencing of the individual on process of decision making ("subjectivity of objectivity") and reduction of influencing of the individual psychosomatic characteristics of the subject (" objectivity of subjectivity ") are offered. The principles are illustrated on mathe...

Memory Effect on Adaptive Decision Making with a Chaotic Semiconductor Laser

Directory of Open Access Journals (Sweden)

Takatomo Mihana

2018-01-01

Full Text Available We investigate the effect of a memory parameter on the performance of adaptive decision making using a tug-of-war method with the chaotic oscillatory dynamics of a semiconductor laser. We experimentally generate chaotic temporal waveforms of the semiconductor laser with optical feedback and apply them for adaptive decision making in solving a multiarmed bandit problem that aims at maximizing the total reward from slot machines whose hit probabilities are dynamically switched. We examine the dependence of making correct decisions on different values of the memory parameter. The degree of adaptivity is found to be enhanced with a smaller memory parameter, whereas the degree of convergence to the correct decision is higher for a larger memory parameter. The relations among the adaptivity, environmental changes, and the difficulties of the problem are also discussed considering the requirement of past decisions. This examination of ultrafast adaptive decision making highlights the importance of memorizing past events and paves the way for future photonic intelligence.

Integrated system of structural health monitoring and intelligent management for a cable-stayed bridge.

Science.gov (United States)

Chen, Bin; Wang, Xu; Sun, Dezhang; Xie, Xu

2014-01-01

It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province). The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

‘Instant Karma’—Moral Decision Making Systems in Digital Games

Directory of Open Access Journals (Sweden)

Tobias Knoll

2018-04-01

Full Text Available Moral decision making systems have long been a popular and widely discussed part of computer games; especially in—but not limited to—role-playing games and other games with strong narrative elements. In this article, an attempt will be made to draw a connection between historic and recent concepts of karma and moral decision making systems in digital games, called ‘karma systems’. At the same time, a detailed analysis of one such system (that of Mass Effect 2 will be provided.

Building simulations supporting decision making in early design – A review

DEFF Research Database (Denmark)

Østergård, Torben; Jensen, Rasmus Lund; Maagaard, Steffen

2016-01-01

The building design community is challenged by continuously increasing energy demands, which are often combined with ambitious goals for indoor environment, for environmental impact, and for building costs. To aid decision-making, building simulation is widely used in the late design stages...... framework that facilitates proactive, intelligent, and experience based building simulation which aid decision making in early design. To find software candidates accommodating this framework, we compare existing software with regard to intended usage, interoperability, complexity, objectives, and ability...

A fuzzy TOPSIS model to evaluate the Business Intelligence competencies of Port Community Systems

Directory of Open Access Journals (Sweden)

Ghazanfari Mehdi

2014-04-01

Full Text Available Evaluation of the Business Intelligence (BI competencies of port community systems before they are bought and deployed is a vital importance for establishment of a decision-support environment for managers. This study proposes a new model which provides a simple approach to the assessment of the BI competencies of port community systems in organization. This approach helps decision-makers to select an enterprise system with appropriate intelligence requirements to support the managers’ decision-making tasks. Thirtyfour criteria for BI specifications are determined from a thorough review of the literature. The proposed model uses the fuzzy TOPSIS technique, which employs fuzzy weights of the criteria and fuzzy judgments of port community systems to compute the evaluation scores and rankings. The application of the model is realized in the evaluation, ranking and selecting of the needed port community systems in a port and maritime organization, in order to validate the proposed model with a real application. With utilizing the proposed model organizations can assess, select, and purchase port community systems which will provide a better decision-support environment for their business systems.

Neural Systems Responding to Degrees of Uncertainty in Human Decision-Making

OpenAIRE

Hsu, Ming; Bhatt, Meghana; Adolphs, Ralph; Tranel, Daniel; Camerer, Colin F.

2005-01-01

Much is known about how people make decisions under varying levels of probability (risk). Less is known about the neural basis of decision-making when probabilities are uncertain because of missing information (ambiguity). In decision theory, ambiguity about probabilities should not affect choices. Using functional brain imaging, we show that the level of ambiguity in choices correlates positively with activation in the amygdala and orbitofrontal cortex, and negatively with a striatal system....

The amygdala and decision-making.

Science.gov (United States)

Gupta, Rupa; Koscik, Timothy R; Bechara, Antoine; Tranel, Daniel

2011-03-01

Decision-making is a complex process that requires the orchestration of multiple neural systems. For example, decision-making is believed to involve areas of the brain involved in emotion (e.g., amygdala, ventromedial prefrontal cortex) and memory (e.g., hippocampus, dorsolateral prefrontal cortex). In this article, we will present findings related to the amygdala's role in decision-making, and differentiate the contributions of the amygdala from those of other structurally and functionally connected neural regions. Decades of research have shown that the amygdala is involved in associating a stimulus with its emotional value. This tradition has been extended in newer work, which has shown that the amygdala is especially important for decision-making, by triggering autonomic responses to emotional stimuli, including monetary reward and punishment. Patients with amygdala damage lack these autonomic responses to reward and punishment, and consequently, cannot utilize "somatic marker" type cues to guide future decision-making. Studies using laboratory decision-making tests have found deficient decision-making in patients with bilateral amygdala damage, which resembles their real-world difficulties with decision-making. Additionally, we have found evidence for an interaction between sex and laterality of amygdala functioning, such that unilateral damage to the right amygdala results in greater deficits in decision-making and social behavior in men, while left amygdala damage seems to be more detrimental for women. We have posited that the amygdala is part of an "impulsive," habit type system that triggers emotional responses to immediate outcomes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Emotion, decision-making and the brain.

Science.gov (United States)

Chang, Luke J; Sanfey, Alan G

2008-01-01

Initial explorations in the burgeoning field of neuroeconomics have highlighted evidence supporting a potential dissociation between a fast automatic system and a slow deliberative controlled system. Growing research in the role of emotion in decision-making has attempted to draw parallels to the automatic system. This chapter will discuss a theoretical framework for understanding the role of emotion in decision-making and evidence supporting the underlying neural substrates. This chapter applies a conceptual framework to understanding the role of emotion in decision-making, and emphasizes a distinction between expected and immediate emotions. Expected emotions refer to anticipated emotional states associated with a given decision that are never actually experienced. Immediate emotions, however, are experienced at the time of decision, and either can occur in response to a particular decision or merely as a result of a transitory fluctuation. This chapter will review research from the neuroeconomics literature that supports a neural dissociation between these two classes of emotion and also discuss a few interpretive caveats. Several lines of research including regret, uncertainty, social decision-making, and moral decision-making have yielded evidence consistent with our formulization--expected and immediate emotions may invoke dissociable neural systems. This chapter provides a more specific conceptualization of the mediating role of emotions in the decision-making process, which has important implications for understanding the interacting neural systems underlying the interface between emotion and cognition--a topic of immediate value to anyone investigating topics within the context of social-cognitive-affective-neuroscience.

Methods and decision making on a Mars rover for identification of fossils

Science.gov (United States)

Eberlein, Susan; Yates, Gigi

1989-01-01

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Applying of forecasting at decision making in power systems

International Nuclear Information System (INIS)

Sapundjiev, G.

2007-01-01

The problems concerning forecast and decision making are analyzed. The typical tasks arising in the forecasting process of the power systems with hierarchical structure formulated and brought to formal description

Hardware-in-the-Loop Simulation of Distributed Intelligent Energy Management System for Microgrids

Directory of Open Access Journals (Sweden)

Dong-Jun Won

2013-07-01

Full Text Available Microgrids are autonomous low-voltage power distribution systems that contain multiple distributed energy resources (DERs and smart loads that can provide power system operation flexibility. To effectively control and coordinate multiple DERs and loads of microgrids, this paper proposes a distributed intelligent management system that employs a multi-agent-based control system so that delicate decision-making functions can be distributed to local intelligent agents. This paper presents the development of a hardware-in-the-loop simulation (HILS system for distributed intelligent management system for microgrids and its promising application to an emergency demand response program. In the developed HILS system, intelligent agents are developed using microcontrollers and ZigBee wireless communication technology. Power system dynamic models are implemented in real-time simulation environments using the Opal-RT system. This paper presents key features of the data communication and management schemes based on multi-agent concepts. The performance of the developed system is tested for emergency demand response program applications.

A Novel Extension Decision-Making Method for Selecting Solar Power Systems

Directory of Open Access Journals (Sweden)

Meng-Hui Wang

2013-01-01

Full Text Available Due to the complex parameters of a solar power system, the designer not only must think about the load demand but also needs to consider the price, weight, and annual power generating capacity (APGC and maximum power of the solar system. It is an important task to find the optimal solar power system with many parameters. Therefore, this paper presents a novel decision-making method based on the extension theory; we call it extension decision-making method (EDMM. Using the EDMM can make it quick to select the optimal solar power system. The paper proposed this method not only to provide a useful estimated tool for the solar system engineers but also to supply the important reference with the installation of solar systems to the consumer.

Artificial intelligence - New tools for aerospace project managers

Science.gov (United States)

Moja, D. C.

1985-01-01

Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

Complex Decision Making Theory and Practice

CERN Document Server

Qudrat-Ullah, Hassan; Spector, J Michael

2007-01-01

The increasingly complex environment of today's world, characterized by technological innovation and global communication, generates myriads of possible and actual interactions while limited physical and intellectual resources severely impinge on decision makers, be it in the public or private domains. At the core of the decision-making process is the need for quality information that allows the decision maker to better assess the impact of decisions in terms of outcomes, nonlinear feedback processes and time delays on the performance of the complex system invoked. This volume is a timely review on the principles underlying complex decision making, the handling of uncertainties in dynamic envrionments and of the various modeling approaches used. The book consists of five parts, each composed of several chapters: I: Complex Decision Making: Concepts, Theories and Empirical Evidence II: Tools and Techniques for Decision Making in Complex Environments and Systems III: System Dynamics and Agent-Based Modeling IV:...

Smart Grid as Multi-layer Interacting System for Complex Decision Makings

Science.gov (United States)

Bompard, Ettore; Han, Bei; Masera, Marcelo; Pons, Enrico

This chapter presents an approach to the analysis of Smart Grids based on a multi-layer representation of their technical, cyber, social and decision-making aspects, as well as the related environmental constraints. In the Smart Grid paradigm, self-interested active customers (prosumers), system operators and market players interact among themselves making use of an extensive cyber infrastructure. In addition, policy decision makers define regulations, incentives and constraints to drive the behavior of the competing operators and prosumers, with the objective of ensuring the global desired performance (e.g. system stability, fair prices). For these reasons, the policy decision making is more complicated than in traditional power systems, and needs proper modeling and simulation tools for assessing "in vitro" and ex-ante the possible impacts of the decisions assumed. In this chapter, we consider the smart grids as multi-layered interacting complex systems. The intricacy of the framework, characterized by several interacting layers, cannot be captured by closed-form mathematical models. Therefore, a new approach using Multi Agent Simulation is described. With case studies we provide some indications about how to develop agent-based simulation tools presenting some preliminary examples.

A Framework for Knowledge Management and Automated Reasoning Applied on Intelligent Transport Systems

OpenAIRE

Feljan, Aneta Vulgarakis; Karapantelakis, Athanasios; Mokrushin, Leonid; Liang, Hongxin; Inam, Rafia; Fersman, Elena; Azevedo, Carlos R. B.; Raizer, Klaus; Souza, Ricardo S.

2017-01-01

Cyber-Physical Systems in general, and Intelligent Transport Systems (ITS) in particular use heterogeneous data sources combined with problem solving expertise in order to make critical decisions that may lead to some form of actions e.g., driver notifications, change of traffic light signals and braking to prevent an accident. Currently, a major part of the decision process is done by human domain experts, which is time-consuming, tedious and error-prone. Additionally, due to the intrinsic n...

Insular neural system controls decision-making in healthy and methamphetamine-treated rats.

Science.gov (United States)

Mizoguchi, Hiroyuki; Katahira, Kentaro; Inutsuka, Ayumu; Fukumoto, Kazuya; Nakamura, Akihiro; Wang, Tian; Nagai, Taku; Sato, Jun; Sawada, Makoto; Ohira, Hideki; Yamanaka, Akihiro; Yamada, Kiyofumi

2015-07-21

Patients suffering from neuropsychiatric disorders such as substance-related and addictive disorders exhibit altered decision-making patterns, which may be associated with their behavioral abnormalities. However, the neuronal mechanisms underlying such impairments are largely unknown. Using a gambling test, we demonstrated that methamphetamine (METH)-treated rats chose a high-risk/high-reward option more frequently and assigned higher value to high returns than control rats, suggestive of changes in decision-making choice strategy. Immunohistochemical analysis following the gambling test revealed aberrant activation of the insular cortex (INS) and nucleus accumbens in METH-treated animals. Pharmacological studies, together with in vivo microdialysis, showed that the insular neural system played a crucial role in decision-making. Moreover, manipulation of INS activation using designer receptor exclusively activated by designer drug technology resulted in alterations to decision-making. Our findings suggest that the INS is a critical region involved in decision-making and that insular neural dysfunction results in risk-taking behaviors associated with altered decision-making.

Lone ranger decision making versus consensus decision making: Descriptive analysis

OpenAIRE

Maite Sara Mashego

2015-01-01

Consensus decision making, concerns group members make decisions together with the requirement of reaching a consensus that is all members abiding by the decision outcome. Lone ranging worked for sometime in a autocratic environment. Researchers are now pointing to consensus decision-making in organizations bringing dividend to many organizations. This article used a descriptive analysis to compare the goodness of consensus decision making and making lone ranging decision management. This art...

Design and Implementation of a General Decision-Making Model in RoboCup Simulation

Directory of Open Access Journals (Sweden)

Changda Wang

2004-09-01

Full Text Available The study of the collaboration, coordination and negotiation among different agents in a multi-agent system (MAS has always been the most challenging yet popular in the research of distributed artificial intelligence. In this paper, we will suggest for RoboCup simulation, a typical MAS, a general decision-making model, rather than define a different algorithm for each tactic (e.g. ball handling, pass, shoot and interception, etc. in soccer games as most RoboCup simulation teams did. The general decision-making model is based on two critical factors in soccer games: the vertical distance to the goal line and the visual angle for the goalpost. We have used these two parameters to formalize the defensive and offensive decisions in RoboCup simulation and the results mentioned above had been applied in NOVAURO®, original name is UJDB, a RoboCup simulation team of Jiangsu University, whose decision-making model, compared with that of Tsinghua University, the world champion team in 2001, is a universal model and easier to be implemented.

THE MAKING OF DECISION MAKING

Directory of Open Access Journals (Sweden)

Leonardo Yuji Tamura

2016-04-01

Full Text Available Quantum Electronics was a Brazilian startup in the 1990's that was acquired by an American equity fund in 2012. They are currently the largest manufacturer of vehicle tracking and infotainment systems. The company was founded by three college friends, who are currently executives at the company: Camilo Santos, Pedro Barbosa and Luana Correa. Edward Hutter was sent by the equity fund to take over the company’s finances, but is having trouble making organizational decisions with his colleagues. As a consultant, I was called to help them improve their decision making process and project prioritization. I adapted and deployed our firm's methodology, but, in the end, its adequacy is shown to be very much in question. The author of this case study intends to explore how actual organizational decisions rely on different decision models and their assumptions, .as well as demonstrate that a decision model is neither absolutely good nor bad as its quality is context dependent.

The psychology of defendant plea decision making.

Science.gov (United States)

Redlich, Allison D; Bibas, Stephanos; Edkins, Vanessa A; Madon, Stephanie

2017-01-01

Every day, thousands of defendants, prosecutors, and defense attorneys must make guilty plea decisions, such as whether to accept a plea offer or proceed to trial. Most defendants opt to plead guilty; approximately 95% of state and federal convictions result from guilty pleas. In light of a newly emerging body of research and recent Supreme Court decisions on guilty pleas, this article asks and answers 2 questions: First, who pleads guilty and why? We describe the characteristics of those who are more or less likely to plead guilty, and examine the reasons why individuals plead guilty instead of proceeding to trial, exploring the cognitive, social influence, and developmental factors that underlie decision making. Second, are defendants' plea decisions valid, in that the decisions are made knowingly, intelligently, voluntarily, and with a factual basis of guilt? That is, do defendants who plead guilty understand and appreciate the conditions and consequences of their pleas, as required by law? Are innocent people induced to plead guilty to crimes they did not commit? We conclude with suggestions to move the field of plea research forward. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

About the methodology of system synthesis of decision-makings and its procedures automation

Directory of Open Access Journals (Sweden)

D. P. Oleynikov

2016-01-01

Full Text Available Purpose. The problem qualitative assessment of technologies and innovations, which cannot be solved without modern methods and decision support systems, is currently particularly relevant. The reason for this is the increasingly increasing amount of heterogeneous information, which should take into account the decision maker. Reduction of the allowable period of decision-making also has a signifi cant impact on this process. These reasons are refl ected in the problems of network-centric warfare, nuclear management, forecasting, and conceptual design. It actualizes the problem of the synthesis of new methods of decision-making that will effectively solve the problem of choice of alternatives in those problem areas where the application of existing methods of decision-making is unfounded or inadmissible. The complexity of the process of creation of new decision-making methods caused by the high degree of utilization of cognitive processes. In accordance with the system-wide development trends the designer in the process of synthesis of the decision-makings should take a system (or group of systems which implements certain cognitive operations. The first step towards the creation of such a group of systems is the development of methodology of the system synthesis of decision-makings.Materials and methods. The scope of research are approaches to the synthesis of systems, and in particular – the synthesis of decision-makings. On the basis of multidimensional analysis and generalization of approach the methodology was developed, which consists of the main stages - goal setting, goal achievement and variations of the target system. Within each of the stages a wide variation of operations is possible to be used, which applied depending on the available data, obtained from the analysis of the subject area. With the use of the methodology obtained a number ofdecision-making methods, and their creation was carried out without

Development of the decision make supporting system on incident management

International Nuclear Information System (INIS)

Kasamatsu, Mizuki; Hanada, Satoshi; Noda, Eisuke

2017-01-01

Decision Make Supporting System is designed to support appropriate decision made by top management in the nuclear severe conditions. With crisis response in nuclear power plant (NPP), information entanglement between sites and control centers during intense situations interfere with prompt and accurate decision making. This research started with that kind of background. In order to solve the issue of the information entanglement, Mitsubishi Heavy Industries, Inc. (MHI) carried out the development of the Decision Make Supporting System and the system applies the technology combining the human factors engineering (HFE) and information and communication technology (ICT). During the crisis response, various commands, reactions and communications in a human system need to be managed. Therefore, the combined HFE method including detailed task analysis, user experience (UX), graphic user interface (GUI) and related human-system interface (HSI) design method is applied to the design of the system. These design results systematize the functions that prevent interference with decision-making in the headquarters for incident management. This new solution as a system enhances the safety improvement of the NPP and contributes to develop the skills and abilities of the resources in the NPP. The system has three key features for supporting emergency situations: 'understanding the situation', 'planning the next action', and 'managing resources'. The system helps commanders and responders to grasp the whole situation and allows them to share information in real time to get a whole picture, and the system accumulates the data of the past events in the chronological order to understand correctly how they happened and plan the next action by using a knowledge database that MHI has been developed. If the unexpected event happens which are not in the incident scenario, the system provides support to formulate alternative strategies and measures. With this

Intelligent decision making in quality management theory and applications

CERN Document Server

Yanık, Seda

2016-01-01

  This book presents recently developed intelligent techniques with applications and theory in the area of quality management. The involved applications of intelligence include techniques such as fuzzy sets, neural networks, genetic algorithms, etc. The book consists of classical quality management topics dealing with intelligent techniques for solving the complex quality management problems. The book will serve as an excellent reference for quality managers, researchers, lecturers and postgraduate students in this area. The authors of the chapters are well-known researchers in the area of quality management.  .

Airline Applications of Business Intelligence Systems

Directory of Open Access Journals (Sweden)

Mihai ANDRONIE

2015-09-01

Full Text Available Airline industry is characterized by large quantities of complex, unstructured and rapid changing data that can be categorized as big data, requiring specialized analysis tools to explore it with the purpose of obtaining useful knowledge as decision support for companies that need to fundament their activities and improve the processes they are carrying on. In this context, business intelligence tools are valuable instruments that can optimally process airline related data so that the activities that are conducted can be optimized to maximize profits, while meeting customer requirements. An airline company that has access to large volumes of data (stored into conventional or big data repositories has two options to extract useful decision support information: processing data by using general-purpose business intelligence systems or processing data by using industry specific business intelligence systems. Each of these two options has both advantages and disadvantages for the airline companies that intend to use them. The present paper presents a comparative study of a number of general-purpose and airline industry specific business intelligence systems, together with their main advantages and disadvantages.

Business intelligence appliances in nuclear plant information system

International Nuclear Information System (INIS)

Bai Zhe; Zou Yuanhao

2012-01-01

With the widely use of information system, the enterprise has accumulated large amount of business data. It is urgent and complicated task to manipulate the massive and complex data collation, dig out the useful knowledge which can assist business managers and technical staff with decision-making and error analysis. At present, the business intelligence is in its initial stage in nuclear power plants (NPP), most of the plants start to show and analyze the data at the end-user interface, then go further with Data Mining gradually. By the basis of Data Warehouse. Online Analytical Processing and Data Mining technology, the data can be extracted, transformed and loaded. After the processing, the data is converted into useful information for plant managers to have different perspectives of decision-making and technical staff to analyse errors. (authors)

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.

System Sketch: A Visualization Tool to Improve Community Decision Making

Science.gov (United States)

Making decisions in coastal and estuarine management requires a comprehensive understanding of the linkages between environmental, social, and economic systems. SystemSketch is a web-based scoping tool designed to assist resource managers in characterizing their systems, explorin...

The role of emotion in clinical decision making: an integrative literature review

OpenAIRE

Kozlowski, Desirée; Hutchinson, Marie; Hurley, John; Rowley, Joanne; Sutherland, Joanna

2017-01-01

Background Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. Methods A systematic search of the bibliographic databases PubMed,...

IDM-PhyChm-Ens: intelligent decision-making ensemble methodology for classification of human breast cancer using physicochemical properties of amino acids.

Science.gov (United States)

Ali, Safdar; Majid, Abdul; Khan, Asifullah

2014-04-01

Development of an accurate and reliable intelligent decision-making method for the construction of cancer diagnosis system is one of the fast growing research areas of health sciences. Such decision-making system can provide adequate information for cancer diagnosis and drug discovery. Descriptors derived from physicochemical properties of protein sequences are very useful for classifying cancerous proteins. Recently, several interesting research studies have been reported on breast cancer classification. To this end, we propose the exploitation of the physicochemical properties of amino acids in protein primary sequences such as hydrophobicity (Hd) and hydrophilicity (Hb) for breast cancer classification. Hd and Hb properties of amino acids, in recent literature, are reported to be quite effective in characterizing the constituent amino acids and are used to study protein foldings, interactions, structures, and sequence-order effects. Especially, using these physicochemical properties, we observed that proline, serine, tyrosine, cysteine, arginine, and asparagine amino acids offer high discrimination between cancerous and healthy proteins. In addition, unlike traditional ensemble classification approaches, the proposed 'IDM-PhyChm-Ens' method was developed by combining the decision spaces of a specific classifier trained on different feature spaces. The different feature spaces used were amino acid composition, split amino acid composition, and pseudo amino acid composition. Consequently, we have exploited different feature spaces using Hd and Hb properties of amino acids to develop an accurate method for classification of cancerous protein sequences. We developed ensemble classifiers using diverse learning algorithms such as random forest (RF), support vector machines (SVM), and K-nearest neighbor (KNN) trained on different feature spaces. We observed that ensemble-RF, in case of cancer classification, performed better than ensemble-SVM and ensemble-KNN. Our

User Driven Data Mining, Visualization and Decision Making for NOAA Observing System and Data Investments

Science.gov (United States)

Austin, M.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) observing system enterprise represents a $2.4B annual investment. Earth observations from these systems are foundational to NOAA's mission to describe, understand, and predict the Earth's environment. NOAA's decision makers are charged with managing this complex portfolio of observing systems to serve the national interest effectively and efficiently. The Technology Planning & Integration for Observation (TPIO) Office currently maintains an observing system portfolio for NOAA's validated user observation requirements, observing capabilities, and resulting data products and services. TPIO performs data analytics to provide NOAA leadership business case recommendations for making sound budgetary decisions. Over the last year, TPIO has moved from massive spreadsheets to intuitive dashboards that enable Federal agencies as well as the general public the ability to explore user observation requirements and environmental observing systems that monitor and predict changes in the environment. This change has led to an organizational data management shift to analytics and visualizations by allowing analysts more time to focus on understanding the data, discovering insights, and effectively communicating the information to decision makers. Moving forward, the next step is to facilitate a cultural change toward self-serve data sharing across NOAA, other Federal agencies, and the public using intuitive data visualizations that answer relevant business questions for users of NOAA's Observing System Enterprise. Users and producers of environmental data will become aware of the need for enhancing communication to simplify information exchange to achieve multipurpose goals across a variety of disciplines. NOAA cannot achieve its goal of producing environmental intelligence without data that can be shared by multiple user communities. This presentation will describe where we are on this journey and will provide examples of

Decision making on fitness landscapes

Science.gov (United States)

Arthur, R.; Sibani, P.

2017-04-01

We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et al. that we call the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures.

Decision Making on Fitness Landscapes

DEFF Research Database (Denmark)

Arthur, Rudy; Sibani, Paolo

2017-01-01

We discuss fitness landscapes and how they can be modified to account for co-evolution. We are interested in using the landscape as a way to model rational decision making in a toy economic system. We develop a model very similar to the Tangled Nature Model of Christensen et. al. that we call...... the Tangled Decision Model. This is a natural setting for our discussion of co-evolutionary fitness landscapes. We use a Monte Carlo step to simulate decision making and investigate two different decision making procedures....

Group decision support system for customer-driven product design

Science.gov (United States)

Lin, Zhihang; Chen, Hang; Chen, Kuen; Che, Ada

2000-10-01

This paper describes the work on the development of a group decision support system for customer driven product design. The customer driven is to develop products, which meet all customer requirements in whole life cycle of products. A process model of decision during product primary design is proposed to formulate the structured, semi-structured and unstructured decision problems. The framework for the decision support system is presented that integrated both advances in the group decision making and distributed artificial intelligent. The system consists of the product primary design tool kit and the collaborative platform with multi-agent structure. The collaborative platform of the system and the product primary design tool kit, including the VOC (Voice of Customer) tool, QFD (Quality Function Deployment) tool, the Conceptual design tool, Reliability analysis tool and the cost and profit forecasting tool, are indicated.

Integrated System of Structural Health Monitoring and Intelligent Management for a Cable-Stayed Bridge

Directory of Open Access Journals (Sweden)

Bin Chen

2014-01-01

Full Text Available It is essential to construct structural health monitoring systems for large important bridges. Zhijiang Bridge is a cable-stayed bridge that was built recently over the Hangzhou Qiantang River (the largest river in Zhejiang Province. The length of Zhijiang Bridge is 478 m, which comprises an arched twin-tower space and a twin-cable plane structure. As an example, the present study describes the integrated system of structural health monitoring and intelligent management for Zhijiang Bridge, which comprises an information acquisition system, data management system, evaluation and decision-making system, and application service system. The monitoring components include the working environment of the bridge and various factors that affect bridge safety, such as the stress and strain of the main bridge structure, vibration, cable force, temperature, and wind speed. In addition, the integrated system includes a forecasting and decision-making module for real-time online evaluation, which provides warnings and makes decisions based on the monitoring information. From this, the monitoring information, evaluation results, maintenance decisions, and warning information can be input simultaneously into the bridge monitoring center and traffic emergency center to share the monitoring data, thereby facilitating evaluations and decision making using the system.

Intelligent Learning System using cognitive science theory and artificial intelligence methods

Energy Technology Data Exchange (ETDEWEB)

Cristensen, D.L.

1986-01-01

This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.

Clinical decision-making and secondary findings in systems medicine.

Science.gov (United States)

Fischer, T; Brothers, K B; Erdmann, P; Langanke, M

2016-05-21

Systems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology (especially systems biology); "big data" statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems medicine knowledge and clinicians working to apply it. This article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through "big data" approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the "death computer," to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their

Decision making in water resource planning: Models and computer graphics

Energy Technology Data Exchange (ETDEWEB)

Fedra, K; Carlsen, A J [ed.

1987-01-01

This paper describes some basic concepts of simulation-based decision support systems for water resources management and the role of symbolic, graphics-based user interfaces. Designed to allow direct and easy access to advanced methods of analysis and decision support for a broad and heterogeneous group of users, these systems combine data base management, system simulation, operations research techniques such as optimization, interactive data analysis, elements of advanced decision technology, and artificial intelligence, with a friendly and conversational, symbolic display oriented user interface. Important features of the interface are the use of several parallel or alternative styles of interaction and display, indlucing colour graphics and natural language. Combining quantitative numerical methods with qualitative and heuristic approaches, and giving the user direct and interactive control over the systems function, human knowledge, experience and judgement are integrated with formal approaches into a tightly coupled man-machine system through an intelligent and easily accessible user interface. 4 drawings, 42 references.

An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

Directory of Open Access Journals (Sweden)

Muhammad Faisal Siddiqui

Full Text Available A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT, principal component analysis (PCA, and least squares support vector machine (LS-SVM are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%. Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities

Artificial intelligence: Neural network model as the multidisciplinary team member in clinical decision support to avoid medical mistakes

Directory of Open Access Journals (Sweden)

Igor Vyacheslavovich Buzaev

2016-09-01

Full Text Available Objective: The continuous uninterrupted feedback system is the essential part of any well-organized system. We propose aLYNX concept that is a possibility to use an artificial intelligence algorithm or a neural network model in decision-making system so as to avoid possible mistakes and to remind the doctors to review tactics once more in selected cases. Method: aLYNX system includes: registry with significant factors, decisions and results; machine learning process based on this registry data; the use of the machine learning results as the adviser. We show a possibility to build a computer adviser with a neural network model for making a choice between coronary aortic bypass surgery (CABG and percutaneous coronary intervention (PCI in order to achieve a higher 5-year survival rate in patients with angina based on the experience of 5107 patients. Results: The neural network was trained by 4679 patients who achieved 5-year survival. Among them, 2390 patients underwent PCI and 2289 CABG. After training, the correlation coefficient (r of the network was 0.74 for training, 0.67 for validation, 0.71 for test and 0.73 for total. Simulation of the neural network function has been performed after training in the two groups of patients with known 5-year outcome. The disagreement rate was significantly higher in the dead patient group than that in the survivor group between neural network model and heart team [16.8% (787/4679 vs. 20.3% (87/428, P = 0.065]. Conclusion: The study shows the possibility to build a computer adviser with a neural network model for making a choice between CABG and PCI in order to achieve a higher 5-year survival rate in patients with angina. Keywords: Coronary artery bypass grafting, Percutaneous coronary intervention, Artificial intelligence, Decision making

Decision Making

Directory of Open Access Journals (Sweden)

Pier Luigi Baldi

2006-06-01

Full Text Available This article points out some conditions which significantly exert an influence upon decision and compares decision making and problem solving as interconnected processes. Some strategies of decision making are also examined.

Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

International Nuclear Information System (INIS)

Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

2017-01-01

Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

Decision making in noisy bistable systems with time-dependent asymmetry

Science.gov (United States)

Nené, Nuno R.; Zaikin, Alexey

2013-01-01

Our work draws special attention to the importance of the effects of time-dependent parameters on decision making in bistable systems. Here, we extend previous studies of the mechanism known as speed-dependent cellular decision making in genetic circuits by performing an analytical treatment of the canonical supercritical pitchfork bifurcation problem with an additional time-dependent asymmetry and control parameter. This model has an analogous behavior to the genetic switch. In the presence of transient asymmetries and fluctuations, slow passage through the critical region in both systems increases substantially the probability of specific decision outcomes. We also study the relevance for attractor selection of reaching maximum values for the external asymmetry before and after the critical region. Overall, maximum asymmetries should be reached at an instant where the position of the critical point allows for compensation of the detrimental effects of noise in retaining memory of the transient asymmetries.

Implementation of the Social Decision-Making Skills Curriculum on Primary Students (Grades 1-3) in Lebanon

Science.gov (United States)

El Hassan, Karma; Mouganie, Zeina

2014-01-01

This study investigated the effect of the Social Decision-Making Skills Curriculum (SDSC) on the emotional intelligence and the prosocial behaviors of primary students in Grades 1-3, in a private school in Lebanon. Students were trained in social problem-solving and social decision-making skills through the implementation of the SDSC. Participants…

Artificial intelligence in cardiology

OpenAIRE

Bonderman, Diana

2017-01-01

Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

Intelligent environmental data warehouse

International Nuclear Information System (INIS)

Ekechukwu, B.

1998-01-01

Making quick and effective decisions in environment management are based on multiple and complex parameters, a data warehouse is a powerful tool for the over all management of massive environmental information. Selecting the right data from a warehouse is an important factor consideration for end-users. This paper proposed an intelligent environmental data warehouse system. It consists of data warehouse to feed an environmental researchers and managers with desire environmental information needs to their research studies and decision in form of geometric and attribute data for study area, and a metadata for the other sources of environmental information. In addition, the proposed intelligent search engine works according to a set of rule, which enables the system to be aware of the environmental data wanted by the end-user. The system development process passes through four stages. These are data preparation, warehouse development, intelligent engine development and internet platform system development. (author)

An intelligent multi-media human-computer dialogue system

Science.gov (United States)

Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.

1988-01-01

Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.

Medical decision making

NARCIS (Netherlands)

Stiggelbout, A.M.; Vries, M. de; Scherer, L.; Keren, G.; Wu, G.

2016-01-01

This chapter presents an overview of the field of medical decision making. It distinguishes the levels of decision making seen in health-care practice and shows how research in judgment and decision making support or improve decision making. Most of the research has been done at the micro level,

Complex Strategic Choices Applying Systemic Planning for Strategic Decision Making

CERN Document Server

Leleur, Steen

2012-01-01

Effective decision making requires a clear methodology, particularly in a complex world of globalisation. Institutions and companies in all disciplines and sectors are faced with increasingly multi-faceted areas of uncertainty which cannot always be effectively handled by traditional strategies. Complex Strategic Choices provides clear principles and methods which can guide and support strategic decision making to face the many current challenges. By considering ways in which planning practices can be renewed and exploring the possibilities for acquiring awareness and tools to add value to strategic decision making, Complex Strategic Choices presents a methodology which is further illustrated by a number of case studies and example applications. Dr. Techn. Steen Leleur has adapted previously established research based on feedback and input from various conferences, journals and students resulting in new material stemming from and focusing on practical application of a systemic approach. The outcome is a coher...

Intelligent Data Analysis in the EMERCOM Information System

Science.gov (United States)

Elena, Sharafutdinova; Tatiana, Avdeenko; Bakaev, Maxim

2017-01-01

The paper describes an information system development project for the Russian Ministry of Emergency Situations (MES, whose international operations body is known as EMERCOM), which was attended by the representatives of both the IT industry and the academia. Besides the general description of the system, we put forward OLAP and Data Mining-based approaches towards the intelligent analysis of the data accumulated in the database. In particular, some operational OLAP reports and an example of multi-dimensional information space based on OLAP Data Warehouse are presented. Finally, we outline Data Mining application to support decision-making regarding security inspections planning and results consideration.

Fuzzy methods in decision making process - A particular approach in manufacturing systems

Science.gov (United States)

Coroiu, A. M.

2015-11-01

We are living in a competitive environment, so we can see and understand that the most of manufacturing firms do the best in order to accomplish meeting demand, increasing quality, decreasing costs, and delivery rate. In present a stake point of interest is represented by the development of fuzzy technology. A particular approach for this is represented through the development of methodologies to enhance the ability to managed complicated optimization and decision making aspects involving non-probabilistic uncertainty with the reason to understand, development, and practice the fuzzy technologies to be used in fields such as economic, engineering, management, and societal problems. Fuzzy analysis represents a method for solving problems which are related to uncertainty and vagueness; it is used in multiple areas, such as engineering and has applications in decision making problems, planning and production. As a definition for decision making process we can use the next one: result of mental processes based upon cognitive process with a main role in the selection of a course of action among several alternatives. Every process of decision making can be represented as a result of a final choice and the output can be represented as an action or as an opinion of choice. Different types of uncertainty can be discovered in a wide variety of optimization and decision making problems related to planning and operation of power systems and subsystems. The mixture of the uncertainty factor in the construction of different models serves for increasing their adequacy and, as a result, the reliability and factual efficiency of decisions based on their analysis. Another definition of decision making process which came to illustrate and sustain the necessity of using fuzzy method: the decision making is an approach of choosing a strategy among many different projects in order to achieve some purposes and is formulated as three different models: high risk decision, usual risk

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

Science.gov (United States)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Trustworthiness and Negative Affect Predict Economic Decision-Making

OpenAIRE

Nguyen, Christopher M.; Koenigs, Michael; Yamada, Torricia H.; Teo, Shu Hao; Cavanaugh, Joseph E.; Tranel, Daniel; Denburg, Natalie L.

2011-01-01

The Ultimatum Game (UG) is a widely used and well-studied laboratory model of economic decision-making. Here, we studied 129 healthy adults and compared demographic (i.e., age, gender, education), cognitive (i.e., intelligence, attention/working memory, speed, language, visuospatial, memory, executive functions), and personality (i.e., “Big Five”, positive affect, negative affect) variables between those with a “rational” versus an “irrational” response pattern on the UG. Our data indicated t...

Robust Inventory System Optimization Based on Simulation and Multiple Criteria Decision Making

Directory of Open Access Journals (Sweden)

Ahmad Mortazavi

2014-01-01

Full Text Available Inventory management in retailers is difficult and complex decision making process which is related to the conflict criteria, also existence of cyclic changes and trend in demand is inevitable in many industries. In this paper, simulation modeling is considered as efficient tool for modeling of retailer multiproduct inventory system. For simulation model optimization, a novel multicriteria and robust surrogate model is designed based on multiple attribute decision making (MADM method, design of experiments (DOE, and principal component analysis (PCA. This approach as a main contribution of this paper, provides a framework for robust multiple criteria decision making under uncertainty.

Business making decisions

Directory of Open Access Journals (Sweden)

Enrique Benjamín Franklin Fincowsky

2011-06-01

Full Text Available People and organizations make better or get wrong as consequence of making decisions. Sometimes making decisions is just a trial and error process. Some others, decisions are good and the results profitable with a few of mistakes, most of the time because it’s considered the experience and the control of a specific field or the good intention of who makes them. Actually, all kinds of decisions bring learning. What is important is the intention, the attitude and the values considered in this process. People from different scenes face many facts and circumstances—almost always out of control—that affect the making decisions process. There is not a unique way to make decisions for all companies in many settings. The person who makes a decision should identify the problem, to solve it later using alternatives and solutions. Even though, follow all the steps it’s not easy as it seems. Looking back the conditions related to the decisions, we can mention the followings: uncertainty, risk and certainty. When people identify circumstances and facts, as well as its effects in a possible situation, they will make decisions with certainty. As long as the information decreases and it becomes ambiguous the risk becomes an important factor in the making decisions process because they are connected to probable objectives (clear or subjective (opinion judgment or intuition. To finish, uncertainty, involves people that make a decision with no or little information about circumstances or criteria with basis

Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.

Science.gov (United States)

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2011-11-01

Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. To develop a clinical decision-support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision-support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k=0.68 (pdiagnosis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery

Directory of Open Access Journals (Sweden)

Shu Tian

2015-01-01

Full Text Available The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a VidEo-Based Intelligent Recognitionand Decision (VEBIRD system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VEBIRD comprises a robust eye (iris detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VEBIRD’s effectiveness.

Towards An Intelligent Model-Based Decision Support System For An Integrated Oil Company (EGPC)

International Nuclear Information System (INIS)

Khorshid, M.; Hassan, H.; Abdel Latife, M.A.

2004-01-01

Decision Support System (DSS) is an interactive, flexible and adaptable computer-based support system specially developed for supporting the solution of unstructured management problems [31] DSS has become widespread for oil industry domain in recent years. The computer-based DSS, which were developed and implemented in oil industry, are used to address the complex short-term planning and operational issues associated with downstream industry. Most of these applications concentrate on the data-centered tools, while the model-centered applications of DSS are still very limited up till now [20]. This study develops an Intelligent Model-Based DSS for an integrated oil company, to help policy makers and petroleum planner in improving the effectiveness of the strategic planning in oil sector. This domain basically imposes semi-structured or unstructured decisions and involves a very complex modeling process

Intelligent Bus Stops in the Flexible Bus Systems

OpenAIRE

Razi Iqbal; Muhammad Usman Ghani

2014-01-01

The purpose of this paper is to discuss Intelligent Bus Stops in a special Demand Responsive Transit (DRT), the Flexible Bus System. These Intelligent Bus Stops are more efficient and information rich than Traditional Bus Stops. The real time synchronization of the Flexible Bus System makes it unique as compared to Traditional Bus Systems. The Main concern is to make Bus Stops intelligent and information rich. Buses are informed about the no. of passengers waiting at the upcoming ...

A Proposed Business Intelligent Framework for Recommender Systems

Directory of Open Access Journals (Sweden)

Sitalakshmi Venkatraman

2017-11-01

Full Text Available In this Internet age, recommender systems (RS have become popular, offering new opportunities and challenges to the business world. With a continuous increase in global competition, e-businesses, information portals, social networks and more, websites are required to become more user-centric and rely on the presence and role of RS in assisting users in better decision making. However, with continuous changes in user interests and consumer behavior patterns that are influenced by easy access to vast information and social factors, raising the quality of recommendations has become a challenge for recommender systems. There is a pressing need for exploring hybrid models of the five main types of RS, namely collaborative, demographic, utility, content and knowledge based approaches along with advancements in Big Data (BD to become more context-aware of the technology and social changes and to behave intelligently. There is a gap in literature with a research focus in this direction. This paper takes a step to address this by exploring a new paradigm of applying business intelligence (BI concepts to RS for intelligently responding to user changes and business complexities. A BI based framework adopting a hybrid methodology for RS is proposed with a focus on enhancing the RS performance. Such a business intelligent recommender system (BIRS can adopt On-line Analytical Processing (OLAP tools and performance monitoring metrics using data mining techniques of BI to enhance its own learning, user profiling and predictive models for making a more useful set of personalised recommendations to its users. The application of the proposed framework to a B2C e-commerce case example is presented.

Knowledge structure representation and automated updates in intelligent information management systems

Science.gov (United States)

Corey, Stephen; Carnahan, Richard S., Jr.

1990-01-01

A continuing effort to apply rapid prototyping and Artificial Intelligence techniques to problems associated with projected Space Station-era information management systems is examined. In particular, timely updating of the various databases and knowledge structures within the proposed intelligent information management system (IIMS) is critical to support decision making processes. Because of the significantly large amounts of data entering the IIMS on a daily basis, information updates will need to be automatically performed with some systems requiring that data be incorporated and made available to users within a few hours. Meeting these demands depends first, on the design and implementation of information structures that are easily modified and expanded, and second, on the incorporation of intelligent automated update techniques that will allow meaningful information relationships to be established. Potential techniques are studied for developing such an automated update capability and IIMS update requirements are examined in light of results obtained from the IIMS prototyping effort.

Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

Science.gov (United States)

Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

2006-01-01

There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

Intelligent color recognition system using micro-controller

International Nuclear Information System (INIS)

Mohd Ashhar Khalid; Khairiah Yazid; Nur Aira Abd Rahman; Azaman Ahmad

2006-01-01

Color is widely used in categorizing the quality of products as well as a marker for automatic selection and discrimination of products. Most of color recognizing process is done manually and due to the fact that human perceived color differently, different of opinion frequently occur. This paper deals with the development of an intelligent color recognition system used for discriminating the ripeness of oil palm fruits into three categories namely ripe, under-ripe and un-ripe. In deciding the categories of fruit a sample belong, a technique of decision making similar to human thinking called neural network has been implemented. Implementation of neural network using a micro-controller is not so common, due to a limited capability in floating point calculation. To overcome the problem, a floating-point co-processor specially designed for micro-controller is used. The paper will report the system design and the network training and implementation methods. The effectiveness of the system compared to human decision method is also reported. (Author)

Bangkok's mass rapid transit system's commuter decision-making process in using integrated smartcards

Directory of Open Access Journals (Sweden)

Peerakan Kaewwongwattana

2016-05-01

Full Text Available This paper studied the decision-making process to use an integrated smartcard ticketing system by Bangkok metropolitan transit commuters. A second-order Confirmatory Factor Analysis using LISREL 9.10 was undertaken on Bangkok commuter's decision-making process on the use of an integrated smartcard system. The sample consisted of 300 Bangkok commuters obtained by accidental sampling using questionnaires with a 5-point Likert scale. The tools in the research questionnaires used scale estimation that achieved a confidence value of 0.84. The research instruments used rating scales measuring information search, alternative choices, and use decision on the 15 variables in the decision-making process which had factor loadings between 0.49 and 0.89 weight elements when sorted in descending order and overall had a high level. Use decision, alternative choices and information search had a factor of 0.89, 0.65 and 0.49, respectively. There was a good fit of the decision-making model to the empirical data (chi-square = 34.55, probability (p = 0.94, df = 49, RMSEA = 0.00, GFI = 0.98, AGFI = 0.96, SRMR = 0.04.

Planning and decision making for aerial robots

CERN Document Server

Bestaoui Sebbane, Yasmina

2014-01-01

This book provides an introduction to the emerging field of planning and decision making for aerial robots. An aerial robot is the ultimate form of Unmanned Aerial Vehicle, an aircraft endowed with built-in intelligence, requiring no direct human control and able to perform a specific task. It must be able to fly within a partially structured environment, to react and adapt to changing environmental conditions and to accommodate for the uncertainty that exists in the physical world. An aerial robot can be termed as a physical agent that exists and flies in the real 3D world, can sense its environment and act on it to achieve specific goals. So throughout this book, an aerial robot will also be termed as an agent.   Fundamental problems in aerial robotics include the tasks of spatial motion, spatial sensing and spatial reasoning. Reasoning in complex environments represents a difficult problem. The issues specific to spatial reasoning are planning and decision making. Planning deals with the trajectory algori...

System Interface for an Integrated Intelligent Safety System (ISS for Vehicle Applications

Directory of Open Access Journals (Sweden)

Mahammad A. Hannan

2010-01-01

Full Text Available This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS that includes an airbag deployment decision system (ADDS and a tire pressure monitoring system (TPMS. A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications.

Ship Domain Model for Multi-ship Collision Avoidance Decision-making with COLREGs Based on Artificial Potential Field

Directory of Open Access Journals (Sweden)

TengFei Wang

2017-03-01

Full Text Available A multi-ship collision avoidance decision-making and path planning formulation is studied in a distributed way. This paper proposes a complete set of solutions for multi-ship collision avoidance in intelligent navigation, by using a top-to-bottom organization to structure the system. The system is designed with two layers: the collision avoidance decision-making and the path planning. Under the general requirements of the International Regulations for Preventing Collisions at Sea (COLREGs, the performance of distributed path planning decision-making for anti-collision is analyzed for both give-way and stand-on ships situations, including the emergency actions taken by the stand-on ship in case of the give-way ship’s fault of collision avoidance measures. The Artificial Potential Field method(APF is used for the path planning in details. The developed APF method combined with the model of ship domain takes the target ships’ speed and course in-to account, so that it can judge the moving characteristics of obstacles more accurately. Simulation results indicate that the system proposed can work effectiveness.

Building consensus in strategic decision-making : system dynamics as a group support system

NARCIS (Netherlands)

Vennix, J.A.M.

1995-01-01

System dynamics was originally founded as a method for modeling and simulating the behavior of industrial systems. In recent years it is increasingly employed as a Group Support System for strategic decision-making groups. The model is constructed in direct interaction with a management team, and

Decision making.

Science.gov (United States)

Chambers, David W

2011-01-01

A decision is a commitment of resources under conditions of risk in expectation of the best future outcome. The smart decision is always the strategy with the best overall expected value-the best combination of facts and values. Some of the special circumstances involved in decision making are discussed, including decisions where there are multiple goals, those where more than one person is involved in making the decision, using trigger points, framing decisions correctly, commitments to lost causes, and expert decision makers. A complex example of deciding about removal of asymptomatic third molars, with and without an EBD search, is discussed.

Models of governance in multihospital systems. Implications for hospital and system-level decision-making.

Science.gov (United States)

Morlock, L L; Alexander, J A

1986-12-01

This study utilizes data from a national survey of 159 multihospital systems in order to describe the types of governance structures currently being utilized, and to compare the policy making process for various types of decisions in systems with different approaches to governance. Survey results indicate that multihospital systems most often use one of three governance models. Forty-one percent of the systems (including 33% of system hospitals) use a parent holding company model in which there is a system-wide corporate governing board and separate governing boards for each member hospital. Twenty-two percent of systems in the sample (but 47% of all system hospitals) utilize what we have termed a modified parent holding company model in which there is one system-wide governing board, but advisory boards are substituted for governing boards at the local hospital level. Twenty-three percent of the sampled systems (including 11% of system hospitals) use a corporate model in which there is one system-wide governing board but no other governing or advisory boards at either the divisional, regional or local hospital levels. A comparison of systems using these three governance approaches found significant variation in terms of system size, ownership and the geographic proximity of member hospitals. In order to examine the relationship between alternative approaches to governance and patterns of decision-making, the three model types were compared with respect to the percentages of systems reporting that local boards, corporate management and/or system-wide corporate boards have responsibility for decision-making in a number of specific issue areas. Study results indicate that, regardless of model type, corporate boards are most likely to have responsibility for decisions regarding the transfer, pledging and sale of assets; the formation of new companies; purchase of assets greater than $100,000; changes in hospital bylaws; and the appointment of local board members. In

A Computerised Business Ethics Expert System -A new approach to improving the ethical quality of business decision-making

Directory of Open Access Journals (Sweden)

Bernie Brenner

2007-06-01

Full Text Available Abstract Where unethical business decision-making arises from failures of ethical perception, there is an important role for ethical training and decision-making tools. These may help business people to consider all relevant issues when assessing the ethical status of potential decisions. Ethical training programmes give business people a basic understanding of the principles which underlie ethical judgements and equip them with many of the necessary skills for dealing with the ethical dilemmas which they face in their jobs. Similarly, ethical decision-making tools may guide managers through the various ethical considerations which are relevant to business decision-making and help them to develop their ethical-perceptual skills. Furthermore, by establishing and reinforcing good ethical decision-making practices, training programmes and decision-making tools may also reduce the incidence of self-consciously unethical decision-making. A new approach to improving the ethical quality of business decision-making by the use of computerized business ethics expert systems is proposed. These systems have the potential to guide business people through a process of ethical evaluation while simultaneously fulfilling an educational role, thus providing many of the benefits of both training programmes and decision-making tools. While the prospect of a computer system which could simply make ethical judgements for business people is both unrealistic and undesirable, a system which leads human decision-makers through a structured assessment process has the potential for genuine benefits. Keywords: Expert Systems, Ethical Decision Making

NOVEL APPROACHES TO MULTI-CRITERIA DECISION MAKING WITH INCOMPLETE INFORMATION SYSTEM

OpenAIRE

Shihu Liu

2013-01-01

Our main work in this study is to make a detailed discussion on the multi-criteria decision making with incomplete information systems. At first, an algorithm is constructed to retrieve the missing criteria values by taking into account the local similarity as well as global similarity of each two alternatives. Then, in view of different evaluation information representation, we establish different making methods for the corresponding completed information system. By transforming interval-va...

A Framework for a General Purpose Intelligent Control System for Particle Accelerators. Phase II Final Report

International Nuclear Information System (INIS)

Westervelt, Robert; Klein, William; Kroupa, Michael; Olsson, Eric; Rothrock, Rick

1999-01-01

Vista Control Systems, Inc. has developed a portable system for intelligent accelerator control. The design is general in scope and is thus configurable to a wide range of accelerator facilities and control problems. The control system employs a multi-layer organization in which knowledge-based decision making is used to dynamically configure lower level optimization and control algorithms

A Spatially Intelligent Public Participation System for the Environmental Impact Assessment Process

Directory of Open Access Journals (Sweden)

Lei Lei

2013-05-01

Full Text Available An environmental impact assessment (EIA is a decision-making process that evaluates the possible significant effects that a proposed project may exert on the environment. The EIA scoping and reviewing stages often involve public participation. Although its importance has long been recognized, public participation in the EIA process is often regarded as ineffective, due to time, budget, resource, technical and procedural constraints, as well as the complexity of environmental information. Geographic Information System (GIS and Volunteer Geographic Information (VGI have the potential to contribute to data collection, sharing and presentation, utilize local user-generated content to benefit decision-making and increase public outreach. This research integrated GIS, VGI, social media tools, data mining and mobile technology to design a spatially intelligent framework that presented and shared EIA information effectively to the public. A spatially intelligent public participative system (SIPPS was also developed as a proof-of-concept of the framework. The research selected the Tehachapi Renewable Transmission Project (TRTP as the pilot study area. Survey questionnaires were designed to collect feedback and conduct evaluation. Results show that SIPPS was able to improve the effectiveness of public participation, promote environmental awareness and achieve good system usability.

Intelligent Integrated Health Management for a System of Systems

Science.gov (United States)

Smith, Harvey; Schmalzel, John; Figueroa, Fernando

2008-01-01

implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3

The role of soft computing in intelligent machines.

Science.gov (United States)

de Silva, Clarence W

2003-08-15

An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

Mediating Data and Building Community for Informed, Intelligent Decision Making for the Polar Regions

Science.gov (United States)

Pulsifer, P. L.; Stieglitz, M.

2017-12-01

that social and community-building aspects are as important as technology. Establishing cyberinfrastructure for informed, intelligent decision making for the polar regions will require an innovative combination of emerging technologies and community-building across stakeholders.

Cultural Factors in Systems Design Decision Making and Action

CERN Document Server

Proctor, Robert W; Yih, Yuehwern

2011-01-01

This book brings together an interdisciplinary group of experts to provide increased understanding of the ways in which cultural differences may influence decision making and action. It brings together current knowledge about decision processes, culture and cognition, design of products and interfaces for human interaction with machines and organizational processes culled from a wide variety of sources and puts them into one comprehensive resource. It examines how to design systems used by individuals from different cultures and accommodate the varied backgrounds that affect the users' decisio

Merging paradigms: Decision Making, Management, and Cognitive Control

DEFF Research Database (Denmark)

Rasmussen, Jens

1996-01-01

The paper discusses the trend in paradigms within decision research, drifting from concepts of decision making in terms of normative models of 'rational decision making, through behavioral models in terms of 'biases' - deviations from rational models, toward models of actual decision making...... behavior, such as the SRK concept, naturalistic decision making, and dynamic decision making.In this evolution, concepts such as decision making, management, and behavioral control merge and a concurrent change in concepts underlying design of systems aiming at control of behavior is visible, from...

Development of a First-of-a-Kind Deterministic Decision-Making Tool for Supervisory Control System

Energy Technology Data Exchange (ETDEWEB)

Cetiner, Sacit M [ORNL; Kisner, Roger A [ORNL; Muhlheim, Michael David [ORNL; Fugate, David L [ORNL

2015-07-01

Decision-making is the process of identifying and choosing alternatives where each alternative offers a different approach or path to move from a given state or condition to a desired state or condition. The generation of consistent decisions requires that a structured, coherent process be defined, immediately leading to a decision-making framework. The overall objective of the generalized framework is for it to be adopted into an autonomous decision-making framework and tailored to specific requirements for various applications. In this context, automation is the use of computing resources to make decisions and implement a structured decision-making process with limited or no human intervention. The overriding goal of automation is to replace or supplement human decision makers with reconfigurable decision- making modules that can perform a given set of tasks reliably. Risk-informed decision making requires a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety systems. The implementation of the probabilistic portion of the decision-making engine of the proposed supervisory control system was detailed in previous milestone reports. Once the control options are identified and ranked based on the likelihood of success, the supervisory control system transmits the options to the deterministic portion of the platform. The deterministic multi-attribute decision-making framework uses variable sensor data (e.g., outlet temperature) and calculates where it is within the challenge state, its trajectory, and margin within the controllable domain using utility functions to evaluate current and projected plant state space for different control decisions. Metrics to be evaluated include stability, cost, time to complete (action), power level, etc. The

Shared decision making

Science.gov (United States)

... page: //medlineplus.gov/ency/patientinstructions/000877.htm Shared decision making To use the sharing features on this page, ... treatment you both support. When to use Shared Decision Making Shared decision making is often used when you ...

Managerial Decision Making in Traffic

Directory of Open Access Journals (Sweden)

Teodor Perić

2003-11-01

Full Text Available Decision-making is defined as a selection of a certain actionamong several alternatives. It is the essence of planning, asin the managerial sense there is no plan until a decision of engagementof resources, reputation and direction of activities ismade. Decision-making is, in fact, only a step in planning, evenwhen it is performed quickly and without special consideration.It is what we all experience every day. It is one of the most fascinatingbiological activities and the subject of frightening implicationsfor the whole human race. Since various techniques improvethe system and the quality of managerial decision-making,they are classified into three assumptions: risk analysis, decision-making trees, and the theory of revealed preference. Allof these are based on the interaction of a certain number of importantvariables out of which many contain the elements ofuncertainty, but maybe also high level of probability.

Hybrid Decision-making Method for Emergency Response System of Unattended Train Operation Metro

Directory of Open Access Journals (Sweden)

Bobo Zhao

2016-04-01

Full Text Available Suitable selection of the emergency alternatives is a critical issue in emergency response system of Unattended Train Operation (UTO metro system of China. However, there is no available method for dispatcher group in Operating Control Center (OCC to evaluate the decision under emergency situation. It was found that the emergency decision making in UTO metro system is relative with the preferences and the importance of multi-dispatcher in emergency. Regarding these factors, this paper presents a hybrid method to determinate the priority weights of emergency alternatives, which aggregates the preference matrix by constructing the emergency response task model based on the Weighted Ordered Weighted Averaging (WOWA operator. This calculation approach derives the importance weights depending on the dispatcher emergency tasks and integrates it into the Ordered Weighted Averaging (OWA operator weights based on a fuzzy membership relation. A case from train fire is given to demonstrate the feasibility and practicability of the proposed methods for Group Multi-Criteria Decision Making (GMCDM in emergency management of UTO metro system. The innovation of this research is paving the way for a systematic emergency decision-making solution which connects the automatic metro emergency response system with the GMCDM theory.

An analysis of medical decision making

International Nuclear Information System (INIS)

Lusted, L.B.

1977-01-01

Medical decision-making studies continue to focus on two questions: How do physicians make decisions and how should physicians make decisions. Researchers pursuing the first question emphasize human cognitive processes and the programming of symbol systems to model the observed human behaviour. Those researchers concentrating on the second question assume that there is a standard of performance against which physicians' decisions can be judged, and to help the physician improve his performance an array of tools is proposed. These tools include decision trees, Bayesian analysis, decision matrices, receiver operating characteristic (ROC) analysis, and cost-benefit considerations including utility measures. Both questions must be answered in an ethical context where ethics and decision analysis are intertwined. (author)

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

Research on efficiency evaluation model of integrated energy system based on hybrid multi-attribute decision-making.

Science.gov (United States)

Li, Yan

2017-05-25

The efficiency evaluation model of integrated energy system, involving many influencing factors, and the attribute values are heterogeneous and non-deterministic, usually cannot give specific numerical or accurate probability distribution characteristics, making the final evaluation result deviation. According to the characteristics of the integrated energy system, a hybrid multi-attribute decision-making model is constructed. The evaluation model considers the decision maker's risk preference. In the evaluation of the efficiency of the integrated energy system, the evaluation value of some evaluation indexes is linguistic value, or the evaluation value of the evaluation experts is not consistent. These reasons lead to ambiguity in the decision information, usually in the form of uncertain linguistic values and numerical interval values. In this paper, the risk preference of decision maker is considered when constructing the evaluation model. Interval-valued multiple-attribute decision-making method and fuzzy linguistic multiple-attribute decision-making model are proposed. Finally, the mathematical model of efficiency evaluation of integrated energy system is constructed.

Business Intelligence: Turning Knowledge into Power

Science.gov (United States)

Endsley, Krista

2009-01-01

Today, many school districts are turning to business intelligence tools to retrieve, organize, and share knowledge for faster analysis and more effective, guided decision making. Business intelligence (BI) tools are the technologies and applications that gather and report information to help an organization's leaders make better decisions. BI…

The application of system dynamics modelling to environmental health decision-making and policy - a scoping review.

Science.gov (United States)

Currie, Danielle J; Smith, Carl; Jagals, Paul

2018-03-27

Policy and decision-making processes are routinely challenged by the complex and dynamic nature of environmental health problems. System dynamics modelling has demonstrated considerable value across a number of different fields to help decision-makers understand and predict the dynamic behaviour of complex systems in support the development of effective policy actions. In this scoping review we investigate if, and in what contexts, system dynamics modelling is being used to inform policy or decision-making processes related to environmental health. Four electronic databases and the grey literature were systematically searched to identify studies that intersect the areas environmental health, system dynamics modelling, and decision-making. Studies identified in the initial screening were further screened for their contextual, methodological and application-related relevancy. Studies deemed 'relevant' or 'highly relevant' according to all three criteria were included in this review. Key themes related to the rationale, impact and limitation of using system dynamics in the context of environmental health decision-making and policy were analysed. We identified a limited number of relevant studies (n = 15), two-thirds of which were conducted between 2011 and 2016. The majority of applications occurred in non-health related sectors (n = 9) including transportation, public utilities, water, housing, food, agriculture, and urban and regional planning. Applications were primarily targeted at micro-level (local, community or grassroots) decision-making processes (n = 9), with macro-level (national or international) decision-making to a lesser degree. There was significant heterogeneity in the stated rationales for using system dynamics and the intended impact of the system dynamics model on decision-making processes. A series of user-related, technical and application-related limitations and challenges were identified. None of the reported limitations or challenges

Risk-based decision-making regarding mixed waste disposal systems

International Nuclear Information System (INIS)

Roberds, W.J.

1991-01-01

This paper reports on an efficient approach that has been developed for making rational and defensible decisions among a variety of options (e.g., remedial actions, engineered barriers designs/operational controls, inventory limitations, site investigations and research) for mixed-waste disposal systems, which consist of multiple interacting sites (active, inactive and/or future) with multiple pathways. Such decisions are based on maximizing the satisfaction of identified objectives (including the reliability vis a vis specified criteria), explicitly considering tradeoffs among objectives as well as uncertainties in the consequences of any option

Dual processing model of medical decision-making

Science.gov (United States)

2012-01-01

Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical

Dual processing model of medical decision-making.

Science.gov (United States)

Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

2012-09-03

Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. We show that physician's beliefs about whether to treat at higher (lower) probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker's threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. We have developed the first dual processing model of medical decision-making that has potential to enrich the current medical decision-making field, which is still to the

Systems thinking, complexity and managerial decision-making: an analytical review.

Science.gov (United States)

Cramp, D G; Carson, E R

2009-05-01

One feature that characterizes the organization and delivery of health care is its inherent complexity. All too often, with so much information and so many activities involved, it is difficult for decision-makers to determine in an objective fashion an appropriate course of action. It would appear that a holistic rather than a reductionist approach would be advantageous. The aim of this paper is to review how formal systems thinking can aid decision-making in complex situations. Consideration is given as to how the use of a number of systems modelling methodologies can help in gaining an understanding of a complex decision situation. This in turn can enhance the possibility of a decision being made in a more rational, explicit and transparent fashion. The arguments and approaches are illustrated using examples taken from the public health arena.

Decision Making with Imperfect Decision Makers

CERN Document Server

Guy, Tatiana Valentine; Wolpert, David H

2012-01-01

Prescriptive Bayesian decision making has reached a high level of maturity and is well-supported algorithmically. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision-making that it should be accepted as an inherent feature of real decision makers living within interacting societies. To date such societies have been investigated from an economic and gametheoretic perspective, and even to a degree from a physics perspective. However, lit

A hybrid fuzzy-ontology based intelligent system to determine level of severity and treatment recommendation for Benign Prostatic Hyperplasia.

Science.gov (United States)

Torshizi, Abolfazl Doostparast; Zarandi, Mohammad Hossein Fazel; Torshizi, Ghazaleh Doostparast; Eghbali, Kamyar

2014-01-01

This paper deals with application of fuzzy intelligent systems in diagnosing severity level and recommending appropriate therapies for patients having Benign Prostatic Hyperplasia. Such an intelligent system can have remarkable impacts on correct diagnosis of the disease and reducing risk of mortality. This system captures various factors from the patients using two modules. The first module determines severity level of the Benign Prostatic Hyperplasia and the second module, which is a decision making unit, obtains output of the first module accompanied by some external knowledge and makes an appropriate treatment decision based on its ontology model and a fuzzy type-1 system. In order to validate efficiency and accuracy of the developed system, a case study is conducted by 44 participants. Then the results are compared with the recommendations of a panel of experts on the experimental data. Then precision and accuracy of the results were investigated based on a statistical analysis. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

Science.gov (United States)

Neilan, James H.; Cross, Charles; Rothhaar, Paul; Tran, Loc; Motter, Mark; Qualls, Garry; Trujillo, Anna; Allen, B. Danette

2016-01-01

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

The neuroscience of social decision-making.

Science.gov (United States)

Rilling, James K; Sanfey, Alan G

2011-01-01

Given that we live in highly complex social environments, many of our most important decisions are made in the context of social interactions. Simple but sophisticated tasks from a branch of experimental economics known as game theory have been used to study social decision-making in the laboratory setting, and a variety of neuroscience methods have been used to probe the underlying neural systems. This approach is informing our knowledge of the neural mechanisms that support decisions about trust, reciprocity, altruism, fairness, revenge, social punishment, social norm conformity, social learning, and competition. Neural systems involved in reward and reinforcement, pain and punishment, mentalizing, delaying gratification, and emotion regulation are commonly recruited for social decisions. This review also highlights the role of the prefrontal cortex in prudent social decision-making, at least when social environments are relatively stable. In addition, recent progress has been made in understanding the neural bases of individual variation in social decision-making.

Design, Development and Implementation of Decision Support Systems for Private Equity Investment

OpenAIRE

Vroomen, Paul

2017-01-01

The objective of this research is to design, develop and implement an intelligent decision support system (IDSS) for making rational private equity investment decisions. (Private equity investments are capital investments in enterprises that are not traded on public equity markets; they include Equity Buy-Out, Venture Capital, and the new Equity Crowd Funding (ECF) asset classes). The design and development of the IDSS requires the integration of investment science (valuation theory, portfoli...

Computational red teaming risk analytics of big-data-to-decisions intelligent systems

CERN Document Server

Abbass, Hussein A

2015-01-01

Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT).  The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines. The author utilizes Gilbert’s principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of  readers. Coherence:  where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blend...

Reasoning methods in medical consultation systems: artificial intelligence approaches.

Science.gov (United States)

Shortliffe, E H

1984-01-01

It has been argued that the problem of medical diagnosis is fundamentally ill-structured, particularly during the early stages when the number of possible explanations for presenting complaints can be immense. This paper discusses the process of clinical hypothesis evocation, contrasts it with the structured decision making approaches used in traditional computer-based diagnostic systems, and briefly surveys the more open-ended reasoning methods that have been used in medical artificial intelligence (AI) programs. The additional complexity introduced when an advice system is designed to suggest management instead of (or in addition to) diagnosis is also emphasized. Example systems are discussed to illustrate the key concepts.

The use of Fuzzy expert system in robots decision-making

International Nuclear Information System (INIS)

Jamaseb, Mehdi; Jafari, Shahram; Montaseri, Farshid; Dadgar, Masoud

2014-01-01

The main issue that is investigated in this paper, is a method for decision making of mobile robots in different conditions for this purpose, we have used expert system. In this way, that the conditions of the robot are analyzed by on expert person a special issue (like following a ball) using knowledge base and suitable decisions will be mode. Then, using this information fuzzy rules well be built, and using its rules, robots decisions can be implemented like an expert person. In this study, we have used delta3d base for implementing expert systems and CLIPS and also we have used NAO for simulation rcssserver3d robot and 3d football simulation have been used for implementing operation program

COMMAND-AND-CONTROL AND MANAGEMENT DECISION MAKING,

Science.gov (United States)

Reports that the development of command-and-con trol systems in support of decision making and action taking has been accomplished by military...methods applicable to management systems. Concludes that the command-and-control type system for top management decision making is a man-machine system having as its core an on going, dynamic operation. (Author)

International Conference on Intelligent and Interactive Systems and Applications

CERN Document Server

Patnaik, Srikanta; Yu, Zhengtao

2017-01-01

This book provides the latest research findings and developments in the field of interactive intelligent systems, addressing diverse areas such as autonomous systems, Internet and cloud computing, pattern recognition and vision systems, mobile computing and intelligent networking, and e-enabled systems. It gathers selected papers from the International Conference on Intelligent and Interactive Systems and Applications (IISA2016) held on June 25–26, 2016 in Shanghai, China. Interactive intelligent systems are among the most important multi-disciplinary research and development domains of artificial intelligence, human–computer interaction, machine learning and new Internet-based technologies. Accordingly, these systems embrace a considerable number of application areas such as autonomous systems, expert systems, mobile systems, recommender systems, knowledge-based and semantic web-based systems, virtual communication environments, and decision support systems, to name a few. To date, research on interactiv...

Decision Making and Cancer

OpenAIRE

Reyna, Valerie F.; Nelson, Wendy L.; Han, Paul K.; Pignone, Michael P.

2015-01-01

We review decision-making along the cancer continuum in the contemporary context of informed and shared decision making, in which patients are encouraged to take a more active role in their health care. We discuss challenges to achieving informed and shared decision making, including cognitive limitations and emotional factors, but argue that understanding the mechanisms of decision making offers hope for improving decision support. Theoretical approaches to decision making that explain cogni...

Application of preference selection index method for decision making over the design stage of production system life cycle

Directory of Open Access Journals (Sweden)

Rajesh Attri

2015-07-01

Full Text Available The life cycle of production system shows the progress of production system from the inception to the termination of the system. During each stage, mainly in the design stage, certain strategic decisions have to be taken. These decisions are more complex as the decision makers have to assess a wide range of alternatives based on a set of conflicting criteria. As the decision making process is found to be unstructured, characterized by domain dependent knowledge, there is a need to apply an efficient multi-criteria decision making (MCDM tool to help the decision makers in making correct decisions. This paper explores the application of a novel MCDM method i.e. Preference selection index (PSI method to solve various decision-making problems that are generally encountered in the design stage of production system life cycle. To prove the potentiality, applicability and accuracy of PSI method in solving decision making problem during the design stage of production system life cycle, five examples are cited from the literature and are compared with the results obtained by the past researchers.

Decision Making Methods in Space Economics and Systems Engineering

Science.gov (United States)

Shishko, Robert

2006-01-01

This viewgraph presentation reviews various methods of decision making and the impact that they have on space economics and systems engineering. Some of the methods discussed are: Present Value and Internal Rate of Return (IRR); Cost-Benefit Analysis; Real Options; Cost-Effectiveness Analysis; Cost-Utility Analysis; Multi-Attribute Utility Theory (MAUT); and Analytic Hierarchy Process (AHP).

Seasonality in communication and collective decision-making in ants.

Science.gov (United States)

Stroeymeyt, N; Jordan, C; Mayer, G; Hovsepian, S; Giurfa, M; Franks, N R

2014-04-07

The ability of animals to adjust their behaviour according to seasonal changes in their ecology is crucial for their fitness. Eusocial insects display strong collective behavioural seasonality, yet the mechanisms underlying such changes are poorly understood. We show that nest preference by emigrating Temnothorax albipennis ant colonies is influenced by a season-specific modulatory pheromone that may help tune decision-making according to seasonal constraints. The modulatory pheromone triggers aversion towards low-quality nests and enhances colony cohesion in summer and autumn, but not after overwintering-in agreement with reports that field colonies split in spring and reunite in summer. Interestingly, we show that the pheromone acts by downgrading the perceived value of marked nests by informed and naive individuals. This contrasts with theories of collective intelligence, stating that accurate collective decision-making requires independent evaluation of options by individuals. The violation of independence highlighted here was accordingly shown to increase error rate during emigrations. However, this is counterbalanced by enhanced cohesion and the transmission of valuable information through the colony. Our results support recent claims that optimal decisions are not necessarily those that maximize accuracy. Other criteria-such as cohesion or reward rate-may be more relevant in animal decision-making.

The functional neuroanatomy of decision-making.

Science.gov (United States)

Rosenbloom, Michael H; Schmahmann, Jeremy D; Price, Bruce H

2012-01-01

Decision-making is a complex executive function that draws on past experience, present goals, and anticipation of outcome, and which is influenced by prevailing and predicted emotional tone and cultural context. Functional imaging investigations and focal lesion studies identify the orbitofrontal, anterior cingulate, and dorsolateral prefrontal cortices as critical to decision-making. The authors review the connections of these prefrontal regions with the neocortex, limbic system, basal ganglia, and cerebellum, highlight current ideas regarding the cognitive processes of decision-making that these networks subserve, and present a novel integrated neuroanatomical model for decision-making. Finally, clinical relevance of this circuitry is illustrated through a discussion of frontotemporal dementia, traumatic brain injury, and sociopathy.

DECISION SUPPORT SYSTEMS IN MILITARY ACTIONS: NECESSITY, POSSIBILITIES AND CONSTRAINTS

Directory of Open Access Journals (Sweden)

Elena ŞUŞNEA

2012-01-01

Full Text Available Nowadays, modern organizations cannot resort to the decision-making process without relying on information and communication technology if they want to be successful. Thus, besides information as an important input of this process, the tools and techniques used by decision-makers are equally important in the support and validation of their decisions. All this is also valid for the military organizations and their specific tasks and activities. A fortiori military commanders face some of the most diff cult and high-stake decision issues meaningful not only at the level of the military, but also for the humankind. Under these circumstances and as a result of an increase in the diversity and complexity of conflict situations, in the information and technology means employed by opponents in warfare and in the amount of information needed to be processed in real time, decision support systems become a necessity. Starting from the aforementioned inevitable requirement, the aim of this article is to emphasize the possibilities and constraints in developing an intelligent decision support system that assists commanders in making scientific decisions on time, under the right circumstances, for the right costs.

Intelligent computing systems emerging application areas

CERN Document Server

Virvou, Maria; Jain, Lakhmi

2016-01-01

This book at hand explores emerging scientific and technological areas in which Intelligent Computing Systems provide efficient solutions and, thus, may play a role in the years to come. It demonstrates how Intelligent Computing Systems make use of computational methodologies that mimic nature-inspired processes to address real world problems of high complexity for which exact mathematical solutions, based on physical and statistical modelling, are intractable. Common intelligent computational methodologies are presented including artificial neural networks, evolutionary computation, genetic algorithms, artificial immune systems, fuzzy logic, swarm intelligence, artificial life, virtual worlds and hybrid methodologies based on combinations of the previous. The book will be useful to researchers, practitioners and graduate students dealing with mathematically-intractable problems. It is intended for both the expert/researcher in the field of Intelligent Computing Systems, as well as for the general reader in t...

DEVELOPMENT OF THE INTELLECTUAL AGENT-ORIENTED SYSTEM FOR DECISION SUPPORT AT ENTERPRISE

Directory of Open Access Journals (Sweden)

G. Chornous

2014-06-01

Full Text Available Actual status of management confirms usefulness and necessity for development of scientific modeling tools for decision-making processes based on distributed artificial intelligence. The paper presents opportunities of the agent – oriented approach to support operative and strategic management decisions at the pharmaceutical enterprise. It is argued that the combination of intelligent agents technology and Data Mining (DM produces a powerful synergistic effect. The basis of the intellectual agent – oriented DSS (AODSS is proposed to put a hybrid approach to the use of DM. Hybrid intelligent AODSS is represented numerous network of small agents, it provides concurrent operation execution, solutions distribution, knowledge management. Agents can be divided into groups: data agents, monitoring agents, agents for solutions search, modeling agents, impact agents and presentations agents. The result of research is development of AODSS created as a multi-level system wherein the project, process and environment levels are intercommunicated. The combination of intelligent technologies in AODSS allows involve rules, cases, a wide range of DM methods and models. The paper proposes a variant of AODSS implementation within the real enterprise IT-infrastructure based on SAP NetWeaver. The analysis results of the semi-commercial operation of the system assures that it can improve managerial decisions inasmuch as accuracy, consistency, flexibility, speed together form the basis of actual efficient solutions.

Management Intelligent Systems : First International Symposium

CERN Document Server

Martínez-López, Francisco; Rodríguez, Juan

2012-01-01

The 2012 International Symposium on Management Intelligent Systems is believed to be the first international forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; i.e., what we propose to be named as Management Intelligent Systems (MiS). The three-day event aimed to bring together researchers interested in this promising interdisciplinary field who came from areas as varied as management, marketing, and business in general, computer science, artificial intelligence, statistics, etc. This volume presents the proceedings of these activities in a collection of contributions with many original approaches. They address diverse Management and Business areas of application such as decision support, segmentation of markets, CRM, product design, service person...

Neuropsychological correlates of decision making in patients with bulimia nervosa.

Science.gov (United States)

Brand, Matthias; Franke-Sievert, Christiane; Jacoby, Georg E; Markowitsch, Hans J; Tuschen-Caffier, Brunna

2007-11-01

In addition to the core psychopathology of bulimia nervosa (BN), patients with BN often show impulsive behavior that has been related to decision making deficits in other patient groups, such as individuals with anorexia nervosa and pathological gamblers. However, it remains unclear whether BN patients also show difficulties in decision making. In this study, 14 patients with BN and 14 healthy comparison subjects, matched for age, gender, education, body mass index, and intelligence, were examined with the Game of Dice Task (M. Brand, E. Fujiwara, et al., 2005), a gambling task that has fixed winning probabilities and explicit rules for gains and losses, as well as with a neuropsychological test battery and personality questionnaires. On the task, the patients with BN chose the disadvantageous alternatives more frequently than did the comparison subjects. Performance on the Game of Dice Task was related to executive functioning but not to other neuropsychological functions, personality, or disease-specific variables in the BN group. Thus, in patients with BN, decision making abnormalities and executive reductions can be demonstrated and might be neuropsychological correlates of the patients' dysfunctional everyday-life decision making behavior. Neurocognitive functions should be considered in the treatment of BN. PsycINFO Database Record (c) 2007 APA, all rights reserved.

Artificial intelligence in cardiology.

Science.gov (United States)

Bonderman, Diana

2017-12-01

Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

Dual processing model of medical decision-making

Directory of Open Access Journals (Sweden)

Djulbegovic Benjamin

2012-09-01

Full Text Available Abstract Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I and/or an analytical, deliberative (system II processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administered to the patient who may or may not have a disease. Methods We developed a mathematical model in which we linked a recently proposed descriptive psychological model of cognition with the threshold model of medical decision-making and show how this approach can be used to better understand decision-making at the bedside and explain the widespread variation in treatments observed in clinical practice. Results We show that physician’s beliefs about whether to treat at higher (lower probability levels compared to the prescriptive therapeutic thresholds obtained via system II processing is moderated by system I and the ratio of benefit and harms as evaluated by both system I and II. Under some conditions, the system I decision maker’s threshold may dramatically drop below the expected utility threshold derived by system II. This can explain the overtreatment often seen in the contemporary practice. The opposite can also occur as in the situations where empirical evidence is considered unreliable, or when cognitive processes of decision-makers are biased through recent experience: the threshold will increase relative to the normative threshold value derived via system II using expected utility threshold. This inclination for the higher diagnostic certainty may, in turn, explain undertreatment that is also documented in the current medical practice. Conclusions We have developed the first dual processing model of medical decision-making that has potential to

Decision-making in the adolescent brain.

Science.gov (United States)

Blakemore, Sarah-Jayne; Robbins, Trevor W

2012-09-01

Adolescence is characterized by making risky decisions. Early lesion and neuroimaging studies in adults pointed to the ventromedial prefrontal cortex and related structures as having a key role in decision-making. More recent studies have fractionated decision-making processes into its various components, including the representation of value, response selection (including inter-temporal choice and cognitive control), associative learning, and affective and social aspects. These different aspects of decision-making have been the focus of investigation in recent studies of the adolescent brain. Evidence points to a dissociation between the relatively slow, linear development of impulse control and response inhibition during adolescence versus the nonlinear development of the reward system, which is often hyper-responsive to rewards in adolescence. This suggests that decision-making in adolescence may be particularly modulated by emotion and social factors, for example, when adolescents are with peers or in other affective ('hot') contexts.

Categorization = Decision Making + Generalization

Science.gov (United States)

Seger, Carol A; Peterson, Erik J.

2013-01-01

We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891

Visual histories of decision processes for collaborative decision making

OpenAIRE

Kozlova, Karine

2016-01-01

Remembering, understanding and reconstructing past activities is a necessary part of any learning, sense-making or decision making process. It is also essential for any collaborative activity. This dissertation investigates the design and evaluation of systems to support decision remembering, understanding and reconstruction by groups and individuals. By conducting three qualitative case studies of small professional groups, we identify the critical activities where history functionality is n...

Dopamine and Stress System Modulation of Sex Differences in Decision Making.

Science.gov (United States)

Georgiou, Polymnia; Zanos, Panos; Bhat, Shambhu; Tracy, J Kathleen; Merchenthaler, Istvan J; McCarthy, Margaret M; Gould, Todd D

2018-01-01

Maladaptive decision making is associated with several neuropsychiatric disorders, including problem gambling and suicidal behavior. The prevalence of these disorders is higher in men vs women, suggesting gender-dependent regulation of their pathophysiology underpinnings. We assessed sex differences in decision making using the rat version of the Iowa gambling task. Female rats identified the most optimal choice from session 1, whereas male rats from session 5. Male, but not female rats, progressively improved their advantageous option responding and surpassed females. Estrus cycle phase did not affect decision making. To test whether pharmacological manipulations targeting the dopaminergic and stress systems affect decision making in a sex-dependent manner, male and female rats received injections of a dopamine D 2 receptor (D 2 R) antagonist (eticlopride), D 2 R agonist (quinpirole), corticotropin-releasing factor 1 (CRF 1 ) antagonist (antalarmin), and α 2 -adrenergic receptor antagonist (yohimbine; used as a pharmacological stressor). Alterations in mRNA levels of D 2 R and CRF 1 were also assessed. Eticlopride decreased advantageous responding in male, but not female rats, whereas quinpirole decreased advantageous responding specifically in females. Yohimbine dose-dependently decreased advantageous responding in female rats, whereas decreased advantageous responding was only observed at higher doses in males. Antalarmin increased optimal choice responding only in female rats. Higher Drd2 and Crhr1 expression in the amygdala were observed in female vs male rats. Higher amygdalar Crhr1 expression was negatively correlated with advantageous responding specifically in females. This study demonstrates the relevance of dopaminergic- and stress-dependent sex differences to maladaptive decision making.

SOLVING OPTIMAL ASSEMBLY LINE CONFIGURATION TASK BY MULTIOBJECTIVE DECISION MAKING METHODS

Directory of Open Access Journals (Sweden)

Ján ČABALA

2017-06-01

Full Text Available This paper deals with looking for the optimal configuration of automated assembly line model placed within Department of Cybernetics and Artificial Intelligence (DCAI. In order to solve this problem, Stateflow model of each configuration was created to simulate the behaviour of particular assembly line configuration. Outputs from these models were used as inputs into the multiobjective decision making process. Multi-objective decision-making methods were subsequently used to find the optimal configuration of assembly line. Paper describes the whole process of solving this task, from building the models to choosing the best configuration. Specifically, the problem was resolved using the experts’ evaluation method for evaluating the weights of every decision-making criterion, while the ELECTRE III, TOPSIS and AGREPREF methods were used for ordering the possible solutions from the most to the least suitable alternative. Obtained results were compared and final solution of this multi-objective decisionmaking problem is chosen.

Dynamical cognitive services for ambient intelligence environments

NARCIS (Netherlands)

Acampora, G.; Loia, V.; Lee, C.-S.; Wang, M.-H.

2009-01-01

Ambient Intelligence systems are more than a simple integration among computer technologies, indeed, their design can strongly depend upon psychology and social sciences aspects describing, analyzing and forecasting the human being status during the system's decision making. Consequently, if from a

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...

A Game-Chain-Based Approach for Decision Making

OpenAIRE

An, Tingyu; Watanabe, tsunami

2009-01-01

Nowadays, with the rapid development of information society, decision-making problems become more and more complicated especially in large scale systems such as infrastructure, environmental and industrial fields, which are usually accompanied by psychological competition between involved parties in a complicated, uncertain and dynamic situation. From a holistic perspective of system, a specific decision-making method which is described as game-chain-based decision making has been proposed in...

Clinical and Business Intelligence: Why It's Important to Your Pharmacy.

Science.gov (United States)

Pinto, Brian; Fox, Brent I

2016-07-01

According to the Healthcare Information Management and Systems Society, "Clinical & Business Intelligence (C&BI) is the use and analysis of data captured in the healthcare setting to directly inform decision-making" (http://www.himss.org/library/clinical-business-intelligence). Some say that it is the right information given to the right person at the right time in the right way. No matter how you define it, the fact remains that timely access, synthesis, and visualization of clinical data have become key to how health professionals make patient care decisions and improve care delivery.

Decision making in midwifery: rationality and intuition.

Science.gov (United States)

Steinhauer, Suyai

2015-04-01

Decision making in midwifery is a complex process that shapes and underpins clinical practice and determines, to a large extent, the quality of care. Effective decision making and professional accountability are central to clinical governance, and being able.to justify all decisions is a professional and legal requirement. At the same time, there is an emphasis in midwifery on shared decision making, and keeping women at the centre of their care, and research reveals that feelings of choice, control and autonomy are central to a positive birth experience. However the extent to which decisions are really shared and care truly woman-centred is debatable and affected by environment and culture. Using a case study of a decision made in clinical practice around amniotomy, this article explores the role of the intuitive thinking system in midwifery decision making, and highlights the importance of involving women in the decision making process.

Nuclear and radiation emergency evaluation and decision-making support system for ministry of environmental protection

International Nuclear Information System (INIS)

Yue Huiguo; Lin Quanyi; Zhang Jiangang

2010-01-01

This article introduces the design features and main functions of The Nuclear and Radiation Emergency Evaluation and Decision Support System. The Ministry of Environmental Protection will construct a complete set of evaluation and decision-making system at the Nuclear Safety Center of Ministry of Environmental Protection to cope with the sudden event. The system will provide a comprehensive technical support for the consequence evaluation and decision-making of anti-terrorism event according to the responsibility of MEP in the sudden event, with the data provided by the MEP's anti-terrorism information platform. (authors)

Moral Behavior as Rule Governed Behavior: Person and System Effects on Moral Decision Making.

Science.gov (United States)

Kurtines, William M.; And Others

Recent approaches to research on moral development have considered the preeminence of situational factors in moral development and moral behavior. An open systems approach emphasizes the interactive effects of person and situation variables on moral decision-making. The interactive effects of three sets of variables on moral decision-making were…

Multiattribute Decision Making Based on Entropy under Interval-Valued Intuitionistic Fuzzy Environment

Directory of Open Access Journals (Sweden)

Yingjun Zhang

2013-01-01

Full Text Available Multiattribute decision making (MADM is one of the central problems in artificial intelligence, specifically in management fields. In most cases, this problem arises from uncertainty both in the data derived from the decision maker and the actions performed in the environment. Fuzzy set and high-order fuzzy sets were proven to be effective approaches in solving decision-making problems with uncertainty. Therefore, in this paper, we investigate the MADM problem with completely unknown attribute weights in the framework of interval-valued intuitionistic fuzzy (IVIF set (IVIFS. We first propose a new definition of IVIF entropy and some calculation methods for IVIF entropy. Furthermore, we propose an entropy-based decision-making method to solve IVIF MADM problems with completely unknown attribute weights. Particular emphasis is put on assessing the attribute weights based on IVIF entropy. Instead of the traditional methods, which use divergence among attributes or the probabilistic discrimination of attributes to obtain attribute weights, we utilize the IVIF entropy to assess the attribute weights based on the credibility of the decision-making matrix for solving the problem. Finally, a supplier selection example is given to demonstrate the feasibility and validity of the proposed MADM method.

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.  

Using reliability analysis to support decision making\\ud in phased mission systems

OpenAIRE

Zhang, Yang; Prescott, Darren

2017-01-01

Due to the environments in which they will operate, future autonomous systems must be capable of reconfiguring quickly and safely following faults or environmental changes. Past research has shown how, by considering autonomous systems to perform phased missions, reliability analysis can support decision making by allowing comparison of the probability of success of different missions following reconfiguration. Binary Decision Diagrams (BDDs) offer fast, accurate reliability analysis that cou...

Decision making under uncertainty

International Nuclear Information System (INIS)

Cyert, R.M.

1989-01-01

This paper reports on ways of improving the reliability of products and systems in this country if we are to survive as a first-rate industrial power. The use of statistical techniques have, since the 1920s, been viewed as one of the methods for testing quality and estimating the level of quality in a universe of output. Statistical quality control is not relevant, generally, to improving systems in an industry like yours, but certainly the use of probability concepts is of significance. In addition, when it is recognized that part of the problem involves making decisions under uncertainty, it becomes clear that techniques such as sequential decision making and Bayesian analysis become major methodological approaches that must be utilized

Applications of artificial intelligence technology to wastewater treatment fields in China

Institute of Scientific and Technical Information of China (English)

QING Xiao-xia; WANG Bo; MENG De-tao

2005-01-01

Current applications of artificial intelligence technology to wastewater treatment in China are summarized. Wastewater treatment plants use expert system mainly in the operation decision-making and fault diagnosis of system operation, use artificial neuron network for system modeling, water quality forecast and soft measure, and use fuzzy control technology for the intelligence control of wastewater treatment process. Finally, the main problems in applying artificial intelligence technology to wastewater treatment in China are analyzed.

Logical Aspects Regarding the Conception of Intelligent Systems

Directory of Open Access Journals (Sweden)

Vasile Mazilescu

2016-07-01

Full Text Available The present paper presents some logical aspects of symbolic AI Systems, applied to the Intelligent Systems design. The basic feature of these systems is represented by the processing of the imprecise and dynamic knowledge involved in the synthesis of some decisions. We consider that the paper tackles an up-to-date and little debated aspect especially in the field of decision fuzzy systems. Knowledge-based systems with real-time functioning bear features that the majority of classic systems do not have: reasoning is evolutionary and non-monotonous due to the dynamic nature of the application, and events can change the status of the expert management system. The management architectures based on symbolic techniques acquire characteristics specific to the domain problem and to the type of intelligent system based on a management knowledge structure.

Marketing Decision Making and Decision Support: Challenges and Perspectives for Successful Marketing Management Support Systems

NARCIS (Netherlands)

G.H. van Bruggen (Gerrit); B. Wierenga (Berend)

2009-01-01

textabstractMarketing management support systems (MMSS) are computer-enabled devices that help marketers to make better decisions. Marketing processes can be quite complex, involving large numbers of variables and mostly outcomes are the results of the actions of many different stakeholders (e.g.,

Uncertain multi-attribute decision making methods and applications

CERN Document Server

Xu, Zeshui

2015-01-01

This book introduces methods for uncertain multi-attribute decision making including uncertain multi-attribute group decision making and their applications to supply chain management, investment decision making, personnel assessment, redesigning products, maintenance services, military system efficiency evaluation. Multi-attribute decision making, also known as multi-objective decision making with finite alternatives, is an important component of modern decision science. The theory and methods of multi-attribute decision making have been extensively applied in engineering, economics, management and military contexts, such as venture capital project evaluation, facility location, bidding, development ranking of industrial sectors and so on. Over the last few decades, great attention has been paid to research on multi-attribute decision making in uncertain settings, due to the increasing complexity and uncertainty of supposedly objective aspects and the fuzziness of human thought. This book can be used as a ref...

Business intelligence and mobile technology research an information systems engineering perspective

CERN Document Server

Laouar, Mohamed Ridda

2014-01-01

All business organizations strive for increasing their growth by seizing new opportunities, reducing enterprise costs, attracting new customers and retaining old customers. In doing so, business intelligence and analytics allow business organizations to make better plans, informed decisions, and monitor their progress towards planned goals and objectives. The more disruptive power of IT technologies comes synergistically. Individual IT technologies do not work in isolation. Business intellige...

Fuzzy-like multiple objective multistage decision making

CERN Document Server

Xu, Jiuping

2014-01-01

Decision has inspired reflection of many thinkers since the ancient times. With the rapid development of science and society, appropriate dynamic decision making has been playing an increasingly important role in many areas of human activity including engineering, management, economy and others. In most real-world problems, decision makers usually have to make decisions sequentially at different points in time and space, at different levels for a component or a system, while facing multiple and conflicting objectives and a hybrid uncertain environment where fuzziness and randomness co-exist in a decision making process. This leads to the development of fuzzy-like multiple objective multistage decision making. This book provides a thorough understanding of the concepts of dynamic optimization from a modern perspective and presents the state-of-the-art methodology for modeling, analyzing and solving the most typical multiple objective multistage decision making practical application problems under fuzzy-like un...

Research and Development of a Network-Based Intelligent Maintenance Information System

Institute of Scientific and Technical Information of China (English)

ZANG Tie-gang; YANG Ming-zhong; GUO Shun-sheng

2003-01-01

A maintenance information system is an important part of equipment management. An intelli gent maintenance information system ( IMIS) is a synthesis of network technology, information technology and intelligent technology. The IMIS is used to finish flexible maintenance decision-making and fast maintenance planning, which helps enterprises to effectively reduce maintenance cost and increase working efficiency. Because the IMIS integrates advanced technologies, its performance is better than a traditional one.The difference between an IMIS and a traditional maintenance information system, and the functions, structure, important realizations, and application of an IMIS are discussed in this paper.

Decision-making support system based on MAS for emergency response to nuclear accidents of marine pressurized-water reactor

International Nuclear Information System (INIS)

Chen Dengke; Zhang Dafa; Jiang Wei; Chen Yonghong

2007-01-01

Emergency decision-making to Marine Pressurized-Water Reactor (MPWR) was severely restricted by the complex environment. To enhance the emergency decision-making ability of MPWR, reducing the effect of emergencies, an emergency Decision-making Support System (DSS) which based on Multi-agent System (MAS) was presented. In the system, the HLA/RTI was used as the support environment, and the structure and the Control Agent (SCA), Analyse Agent (AA), Countermeasure Agent (CA), Evaluation Agent (EVA) and Environment Agent (ENA) were designed. The MAS were with the characteristics of autonomy, reactivity and initiative, which were fully used in the system to make effective decision for emergencies. (authors)

A qualitative study of systemic influences on paramedic decision making: care transitions and patient safety.

Science.gov (United States)

O'Hara, Rachel; Johnson, Maxine; Siriwardena, A Niroshan; Weyman, Andrew; Turner, Janette; Shaw, Deborah; Mortimer, Peter; Newman, Chris; Hirst, Enid; Storey, Matthew; Mason, Suzanne; Quinn, Tom; Shewan, Jane

2015-01-01

Paramedics routinely make critical decisions about the most appropriate care to deliver in a complex system characterized by significant variation in patient case-mix, care pathways and linked service providers. There has been little research carried out in the ambulance service to identify areas of risk associated with decisions about patient care. The aim of this study was to explore systemic influences on decision making by paramedics relating to care transitions to identify potential risk factors. An exploratory multi-method qualitative study was conducted in three English National Health Service (NHS) Ambulance Service Trusts, focusing on decision making by paramedic and specialist paramedic staff. Researchers observed 57 staff across 34 shifts. Ten staff completed digital diaries and three focus groups were conducted with 21 staff. Nine types of decision were identified, ranging from emergency department conveyance and specialist emergency pathways to non-conveyance. Seven overarching systemic influences and risk factors potentially influencing decision making were identified: demand; performance priorities; access to care options; risk tolerance; training and development; communication and feedback and resources. Use of multiple methods provided a consistent picture of key systemic influences and potential risk factors. The study highlighted the increased complexity of paramedic decisions and multi-level system influences that may exacerbate risk. The findings have implications at the level of individual NHS Ambulance Service Trusts (e.g. ensuring an appropriately skilled workforce to manage diverse patient needs and reduce emergency department conveyance) and at the wider prehospital emergency care system level (e.g. ensuring access to appropriate patient care options as alternatives to the emergency department). © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

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 perc...... representation of system properties in a multilevel flow model is described to provide a basis for an integrated control system design.......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...

Design of nuclear emergency decision-making support system based on the results of radiation monitoring

International Nuclear Information System (INIS)

Zheng Qiyan; Zhang Lijun; Huang Weiqi; Chen Lin

2010-01-01

For nuclear emergency decision-making support system based on the results of radiation monitoring, its main assignment is receiving radiation monitoring data and analyzing them, to accomplish some works such as environment influence evaluation, dose assessment for emergency responder, decision-making analyzing and effectiveness evaluation for emergency actions, etc.. This system is made up of server, communication terminal, data-analyzing terminal, GPRS modules, printer, and so on. The whole system make of a LAN. The system's software is made up of six subsystems: data-analyzing subsystem, reporting subsystem, GIS subsystem, communication subsystem, user-managing subsystem and data-base. (authors)

Decision making and cancer.

Science.gov (United States)

Reyna, Valerie F; Nelson, Wendy L; Han, Paul K; Pignone, Michael P

2015-01-01

We review decision making along the cancer continuum in the contemporary context of informed and shared decision making in which patients are encouraged to take a more active role in their health care. We discuss challenges to achieving informed and shared decision making, including cognitive limitations and emotional factors, but argue that understanding the mechanisms of decision making offers hope for improving decision support. Theoretical approaches to decision making that explain cognition, emotion, and their interaction are described, including classical psychophysical approaches, dual-process approaches that focus on conflicts between emotion versus cognition (or reason), and modern integrative approaches such as fuzzy-trace theory. In contrast to the earlier emphasis on rote use of numerical detail, modern approaches emphasize understanding the bottom-line gist of options (which encompasses emotion and other influences on meaning) and retrieving relevant social and moral values to apply to those gist representations. Finally, research on interventions to support better decision making in clinical settings is reviewed, drawing out implications for future research on decision making and cancer. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Multi-disciplinary decision making in general practice.

Science.gov (United States)

Kirby, Ann; Murphy, Aileen; Bradley, Colin

2018-04-09

Purpose Internationally, healthcare systems are moving towards delivering care in an integrated manner which advocates a multi-disciplinary approach to decision making. Such an approach is formally encouraged in the management of Atrial Fibrillation patients through the European Society of Cardiology guidelines. Since the emergence of new oral anticoagulants switching between oral anticoagulants (OACs) has become prevalent. This case study considers the role of multi-disciplinary decision making, given the complex nature of the agents. The purpose of this paper is to explore Irish General Practitioners' (GPs) experience of switching between all OACs for Arial Fibrillation (AF) patients; prevalence of multi-disciplinary decision making in OAC switching decisions and seeks to determine the GP characteristics that appear to influence the likelihood of multi-disciplinary decision making. Design/methodology/approach A probit model is used to determine the factors influencing multi-disciplinary decision making and a multinomial logit is used to examine the factors influencing who is involved in the multi-disciplinary decisions. Findings Results reveal that while some multi-disciplinary decision-making is occurring (64 per cent), it is not standard practice despite international guidelines on integrated care. Moreover, there is a lack of patient participation in the decision-making process. Female GPs and GPs who have initiated prescriptions for OACs are more likely to engage in multi-disciplinary decision-making surrounding switching OACs amongst AF patients. GPs with training practices were less likely to engage with cardiac consultants and those in urban areas were more likely to engage with other (non-cardiac) consultants. Originality/value For optimal decision making under uncertainty multi-disciplinary decision-making is needed to make a more informed judgement and to improve treatment decisions and reduce the opportunity cost of making the wrong decision.

The conceptual definition of a crisis management decision support system CMDSS

International Nuclear Information System (INIS)

Schenker-Wicki, A.G.M.

1990-01-01

The Institute for Automation and Operations Research at the University of Fribourg has been charged by the Swiss government to design a concept for a Crisis Management Decision Support System CMDSS to evaluate acceptable countermeasures to reduce ingestion dose after an accidental release of radioactivity and to implement a prototype. The study is divided in two parts. In the first part all the necessary modules and techniques for efficient decision making, based on the most recent developments in decision theory, as well as the necessary structuring of the decision making process are discussed, while in the second part the plausibility of the evaluated system is tested using a case study. For the time being no empirical research has been carried out. The decision making concept presented in this book comprehends decision making on two different levels, a technical and a political one. The division of decision power corresponds to the Swiss legal prescriptions for accidental release of radioactivity. To guarantee decisions of high quality, as many countermeasures as possible have to be presented to the decision makers. Due to the difficulty of evaluating all the possible countermeasures an expert-system is provided for the decision makers to generate the space of alternatives. The use of an expert-system should further help to reduce systematically the huge amount of information which is characteristic in crises situations. To support the comparison and ranking of the different alternatives a multi-criteria approach, the PROMETHEE method, which is based upon outranking relationships, is used. Due to the complexity of the decision making process, its poorly defined mathematical context and the unwillingness of the decision makers to use a method which requires defined substitution rates, decision methods based on utility theory will not be applied in this study. The outranking approach presented in this book provides its users with more transparent and intelligible

Dual processing model of medical decision-making

OpenAIRE

Djulbegovic, Benjamin; Hozo, Iztok; Beckstead, Jason; Tsalatsanis, Athanasios; Pauker, Stephen G

2012-01-01

Abstract Background Dual processing theory of human cognition postulates that reasoning and decision-making can be described as a function of both an intuitive, experiential, affective system (system I) and/or an analytical, deliberative (system II) processing system. To date no formal descriptive model of medical decision-making based on dual processing theory has been developed. Here we postulate such a model and apply it to a common clinical situation: whether treatment should be administe...

Single-photon decision maker

Science.gov (United States)

Naruse, Makoto; Berthel, Martin; Drezet, Aurélien; Huant, Serge; Aono, Masashi; Hori, Hirokazu; Kim, Song-Ju

2015-08-01

Decision making is critical in our daily lives and for society in general and is finding evermore practical applications in information and communication technologies. Herein, we demonstrate experimentally that single photons can be used to make decisions in uncertain, dynamically changing environments. Using a nitrogen-vacancy in a nanodiamond as a single-photon source, we demonstrate the decision-making capability by solving the multi-armed bandit problem. This capability is directly and immediately associated with single-photon detection in the proposed architecture, leading to adequate and adaptive autonomous decision making. This study makes it possible to create systems that benefit from the quantum nature of light to perform practical and vital intelligent functions.

Fundamental issues of rationalization in corporate decision-making

OpenAIRE

Marek Jacek Stankiewicz

2010-01-01

The paper deals with the problems of the improvement of the decision-making process that is composed of two sub-systems: preparations for making a decision and taking it. Based on the multi-aspect characteristics of the essence and conditions of the decision-making process a referential model of decision-making has been proposed. The model assumes the existence of two principles that apparently may seem contradictory – the principle of rationality and the principle of creative uniqueness. Dec...

Leveraging business intelligence to make better decisions: Part II.

Science.gov (United States)

Reimers, Mona

2014-01-01

This article is the second in a series about business intelligence (BI) in a medical practice. The first article reviewed the evolution of data reporting within the industry and provided some examples of how BI concepts differ from the reports available in the menus of our software systems, or the dashboards and scorecards practices have implemented. This article will discuss how to begin a BI initiative for front-end medical practice staffers that will create tools they can use to reduce errors and increase efficiency throughout their workday. This type of BI rollout can allow practices to get started with very little financial investment, gain enthusiasm from end users, and achieve a quick return on investment. More examples of successful BI projects in medical practices are discussed to help illustrate BI concepts.

HOW TO MAKE ANALYSIS WORK IN BUSINESS INTELLIGENCE SOFTWARE

OpenAIRE

Axner, Dr Lilit

2009-01-01

Competitive Intelligence (CI) has been defined by many authors. These definitions do have certain differences but all of them have a main common feature: They put the accent on the analysis. The most precise definition is given by the Society for Competitive Intelligence Professionals (SCIP): “A systematic and ethical program for gathering, analyzing, and managing external information that can affect your company’s plans, decisions, and operations”. Business Intelligence (BI) is much broader ...

Decision Making Under Uncertainty

Science.gov (United States)

2010-11-01

A sound approach to rational decision making requires a decision maker to establish decision objectives, identify alternatives, and evaluate those...often violate the axioms of rationality when making decisions under uncertainty. The systematic description of such observations may lead to the...which leads to “anchoring” on the initial value. The fact that individuals have been shown to deviate from rationality when making decisions

Affordances and Constraints of Intelligent Decision Support for Military Command and Control : Three Case Studies of Support Systems

OpenAIRE

Leifler, Ola

2011-01-01

Researchers in military command and control (C2) have for several decades sought to help commanders by introducing automated, intelligent decision support systems. These systems are still not widely used, however, and some researchers argue that this may be due to those problems that are inherent in the relationship between the affordances of technology and the requirements by the specific contexts of work in military C2. In this thesis, we study some specific properties of three support tech...

Decision Making in Action

Science.gov (United States)

Orasanu, Judith; Statler, Irving C. (Technical Monitor)

1994-01-01

The importance of decision-making to safety in complex, dynamic environments like mission control centers and offshore installations has been well established. NASA-ARC has a program of research dedicated to fostering safe and effective decision-making in the manned spaceflight environment. Because access to spaceflight is limited, environments with similar characteristics, including aviation and nuclear power plants, serve as analogs from which space-relevant data can be gathered and theories developed. Analyses of aviation accidents cite crew judgement and decision making as causes or contributing factors in over half of all accidents. A similar observation has been made in nuclear power plants. Yet laboratory research on decision making has not proven especially helpful in improving the quality of decisions in these kinds of environments. One reason is that the traditional, analytic decision models are inappropriate to multidimensional, high-risk environments, and do not accurately describe what expert human decision makers do when they make decisions that have consequences. A new model of dynamic, naturalistic decision making is offered that may prove useful for improving decision making in complex, isolated, confined and high-risk environments. Based on analyses of crew performance in full-mission simulators and accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation. Effective crew decision making and overall performance are mediated by crew communication. Communication

DEVELOPMENT OF THE INTELLECTUAL AGENT-ORIENTED SYSTEM FOR DECISION SUPPORT AT ENTERPRISE

OpenAIRE

G. Chornous

2014-01-01

Actual status of management confirms usefulness and necessity for development of scientific modeling tools for decision-making processes based on distributed artificial intelligence. The paper presents opportunities of the agent – oriented approach to support operative and strategic management decisions at the pharmaceutical enterprise. It is argued that the combination of intelligent agents technology and Data Mining (DM) produces a powerful synergistic effect. The basis of the intellectual ...

Requirement analysis for autonomous systems and intelligent ...

African Journals Online (AJOL)

user

Danish Power System and a requirement analysis for the use of intelligent agents and ..... tries to make an optimal islanding plan at this state and tries to blackstart. ... 4 Foundation for Physical Intelligent Agents (FIPA): http://www.fipa.org ...

Argumentative SOX Compliant and Quality Decision Support Intelligent Expert System over the Suppliers Selection Process

Directory of Open Access Journals (Sweden)

Jesus Angel Fernandez Canelas

2013-01-01

Full Text Available The objective of this paper is to define a decision support system over SOX (Sarbanes-Oxley Act compatibility and quality of the Suppliers Selection Process based on Artificial Intelligence and Argumentation Theory knowledge and techniques. The present SOX Law, in effect nowadays, was created to improve financial government control over US companies. This law is a factor standard out United States due to several factors like present globalization, expansion of US companies, or key influence of US stock exchange markets worldwide. This paper constitutes a novel approach to this kind of problems due to following elements: (1 it has an optimized structure to look for the solution, (2 it has a dynamic learning method to handle court and control gonvernment bodies decisions, (3 it uses fuzzy knowledge to improve its performance, and (4 it uses its past accumulated experience to let the system evolve far beyond its initial state.

Research on comprehensive decision-making of PV power station connecting system

Science.gov (United States)

Zhou, Erxiong; Xin, Chaoshan; Ma, Botao; Cheng, Kai

2018-04-01

In allusion to the incomplete indexes system and not making decision on the subjectivity and objectivity of PV power station connecting system, based on the combination of improved Analytic Hierarchy Process (AHP), Criteria Importance Through Intercriteria Correlation (CRITIC) as well as grey correlation degree analysis (GCDA) is comprehensively proposed to select the appropriate system connecting scheme of PV power station. Firstly, indexes of PV power station connecting system are divided the recursion order hierarchy and calculated subjective weight by the improved AHP. Then, CRITIC is adopted to determine the objective weight of each index through the comparison intensity and conflict between indexes. The last the improved GCDA is applied to screen the optimal scheme, so as to, from the subjective and objective angle, select the connecting system. Comprehensive decision of Xinjiang PV power station is conducted and reasonable analysis results are attained. The research results might provide scientific basis for investment decision.

Design and implementation of the standards-based personal intelligent self-management system (PICS).

Science.gov (United States)

von Bargen, Tobias; Gietzelt, Matthias; Britten, Matthias; Song, Bianying; Wolf, Klaus-Hendrik; Kohlmann, Martin; Marschollek, Michael; Haux, Reinhold

2013-01-01

Against the background of demographic change and a diminishing care workforce there is a growing need for personalized decision support. The aim of this paper is to describe the design and implementation of the standards-based personal intelligent care systems (PICS). PICS makes consistent use of internationally accepted standards such as the Health Level 7 (HL7) Arden syntax for the representation of the decision logic, HL7 Clinical Document Architecture for information representation and is based on a open-source service-oriented architecture framework and a business process management system. Its functionality is exemplified for the application scenario of a patient suffering from congestive heart failure. Several vital signs sensors provide data for the decision support system, and a number of flexible communication channels are available for interaction with patient or caregiver. PICS is a standards-based, open and flexible system enabling personalized decision support. Further development will include the implementation of components on small computers and sensor nodes.

Decision making uncertainty, imperfection, deliberation and scalability

CERN Document Server

Kárný, Miroslav; Wolpert, David

2015-01-01

This volume focuses on uncovering the fundamental forces underlying dynamic decision making among multiple interacting, imperfect and selfish decision makers. The chapters are written by leading experts from different disciplines, all considering the many sources of imperfection in decision making, and always with an eye to decreasing the myriad discrepancies between theory and real world human decision making. Topics addressed include uncertainty, deliberation cost and the complexity arising from the inherent large computational scale of decision making in these systems. In particular, analyses and experiments are presented which concern: • task allocation to maximize “the wisdom of the crowd”; • design of a society of “edutainment” robots who account for one anothers’ emotional states; • recognizing and counteracting seemingly non-rational human decision making; • coping with extreme scale when learning causality in networks; • efficiently incorporating expert knowledge in personalized...

Prospective Architectures for Onboard vs Cloud-Based Decision Making for Unmanned Aerial Systems

Science.gov (United States)

Sankararaman, Shankar; Teubert, Christopher

2017-01-01

This paper investigates propsective architectures for decision-making in unmanned aerial systems. When these unmanned vehicles operate in urban environments, there are several sources of uncertainty that affect their behavior, and decision-making algorithms need to be robust to account for these different sources of uncertainty. It is important to account for several risk-factors that affect the flight of these unmanned systems, and facilitate decision-making by taking into consideration these various risk-factors. In addition, there are several technical challenges related to autonomous flight of unmanned aerial systems; these challenges include sensing, obstacle detection, path planning and navigation, trajectory generation and selection, etc. Many of these activities require significant computational power and in many situations, all of these activities need to be performed in real-time. In order to efficiently integrate these activities, it is important to develop a systematic architecture that can facilitate real-time decision-making. Four prospective architectures are discussed in this paper; on one end of the spectrum, the first architecture considers all activities/computations being performed onboard the vehicle whereas on the other end of the spectrum, the fourth and final architecture considers all activities/computations being performed in the cloud, using a new service known as Prognostics as a Service that is being developed at NASA Ames Research Center. The four different architectures are compared, their advantages and disadvantages are explained and conclusions are presented.

Environmental Decision Making and Information Technology: Issues Assessment

Energy Technology Data Exchange (ETDEWEB)

Barg, S.; Fletcher, T.; Mechling, J.; Tonn, B.; Turner, R.

1999-05-01

This report presents a summary of the Information Technology and Environmental Decision Making Workshop that was held at Harvard University, October 1-3, 1998. Over sixty participants from across the US took part in discussions that focused on the current practice of using information technology to support environmental decision making and on future considerations of information technology development, information policies, and data quality issues in this area. Current practice is focusing on geographic information systems and visualization tools, Internet applications, and data warehousing. In addition, numerous organizations are developing environmental enterprise systems to integrate environmental information resources. Plaguing these efforts are issues of data quality (and public trust), system design, and organizational change. In the future, much effort needs to focus on building community-based environmental decision-making systems and processes, which will be a challenge given that exactly what needs to be developed is largely unknown and that environmental decision making in this arena has been characterized by a high level of conflict. Experimentation and evaluation are needed to contribute to efficient and effective learning about how best to use information technology to improve environmental decision making.