Use of agent based simulation for traffic safety assessment

CSIR Research Space (South Africa)

Conradie, Dirk CU

2008-07-01

Full Text Available This paper describes the development of an agent based Computational Building Simulation (CBS) tool, termed KRONOS that is being used to work on advanced research questions such as traffic safety assessment and user behaviour in buildings...

Agent-based Simulation of Reactive, Pro-active, and Social Animal Behaviour

NARCIS (Netherlands)

Jonker, C.M.; Treur, J.; Mira, J.

1998-01-01

In this paper it is shown how animal behaviour can be simulated in an agent-based manner. Different models are shown for different types of behaviour, varying from purely reactive behaviour to pro-active and social behaviour. The compositional development method for multi-agent systems DESIRE and

A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass

Directory of Open Access Journals (Sweden)

Jesús M. Sánchez

2016-08-01

Full Text Available Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation combines scenario-guided agents and humans equipped with Google Glass that coexist in a shared virtual space and jointly perform simulations. The paper proposes an architecture for participatory multiagent simulation in order to combine devices (Google Glass and/or smartphones with an agent-based social simulator and indoor tracking services.

Simulating classroom lessons : an agent-based attempt

OpenAIRE

Ingram, Fred; Brooks, Roger John

2018-01-01

This is an interim report on a project to construct an agent-based simulation that reproduces some of the interactions between students and their teacher in classroom lessons. In a pilot study, the activities of 67 students and 7 teachers during 40 lessons were recorded using a data collection instrument that currently captures 17 student states and 15 teacher states. These data enabled various conceptual models to be explored, providing empirical values and distributions for the model parame...

Efficient graph-based dynamic load-balancing for parallel large-scale agent-based traffic simulation

NARCIS (Netherlands)

Xu, Y.; Cai, W.; Aydt, H.; Lees, M.; Tolk, A.; Diallo, S.Y.; Ryzhov, I.O.; Yilmaz, L.; Buckley, S.; Miller, J.A.

2014-01-01

One of the issues of parallelizing large-scale agent-based traffic simulations is partitioning and load-balancing. Traffic simulations are dynamic applications where the distribution of workload in the spatial domain constantly changes. Dynamic load-balancing at run-time has shown better efficiency

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

Science.gov (United States)

Jaxa-Rozen, M.

2016-12-01

The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

Towards a standard model for research in agent-based modeling and simulation

Directory of Open Access Journals (Sweden)

Nuno Fachada

2015-11-01

Full Text Available Agent-based modeling (ABM is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. ABMs are very sensitive to implementation details. Thus, it is very easy to inadvertently introduce changes which modify model dynamics. Such problems usually arise due to the lack of transparency in model descriptions, which constrains how models are assessed, implemented and replicated. In this paper, we present PPHPC, a model which aims to serve as a standard in agent based modeling research, namely, but not limited to, conceptual model specification, statistical analysis of simulation output, model comparison and parallelization studies. This paper focuses on the first two aspects (conceptual model specification and statistical analysis of simulation output, also providing a canonical implementation of PPHPC. The paper serves as a complete reference to the presented model, and can be used as a tutorial for simulation practitioners who wish to improve the way they communicate their ABMs.

Design and simulation of material-integrated distributed sensor processing with a code-based agent platform and mobile multi-agent systems.

Science.gov (United States)

Bosse, Stefan

2015-02-16

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques.

Design and Simulation of Material-Integrated Distributed Sensor Processing with a Code-Based Agent Platform and Mobile Multi-Agent Systems

Directory of Open Access Journals (Sweden)

Stefan Bosse

2015-02-01

Full Text Available Multi-agent systems (MAS can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques.

Agent Based Simulation of Group Emotions Evolution and Strategy Intervention in Extreme Events

Directory of Open Access Journals (Sweden)

Bo Li

2014-01-01

Full Text Available Agent based simulation method has become a prominent approach in computational modeling and analysis of public emergency management in social science research. The group emotions evolution, information diffusion, and collective behavior selection make extreme incidents studies a complex system problem, which requires new methods for incidents management and strategy evaluation. This paper studies the group emotion evolution and intervention strategy effectiveness using agent based simulation method. By employing a computational experimentation methodology, we construct the group emotion evolution as a complex system and test the effects of three strategies. In addition, the events-chain model is proposed to model the accumulation influence of the temporal successive events. Each strategy is examined through three simulation experiments, including two make-up scenarios and a real case study. We show how various strategies could impact the group emotion evolution in terms of the complex emergence and emotion accumulation influence in extreme events. This paper also provides an effective method of how to use agent-based simulation for the study of complex collective behavior evolution problem in extreme incidents, emergency, and security study domains.

RANA, a real-time multi-agent system simulator

DEFF Research Database (Denmark)

Jørgensen, Søren Vissing; Demazeau, Yves; Hallam, John

2016-01-01

for individualisation and abstraction while retaining efficiency. Events are managed by the C++ simulator core. Full run state can be recorded for post-processed visualisation or analysis. The new tool is demonstrated in three different cases: a mining robot simulation, which is purely action based; an agent......-based setup that is verifies the high precision exhibited by RANAs simulation core; and a state-based firefly-like agent simulation that models real-time responses to fellow agents' signals, in which event propagation and reception affect the result of the simulation....

Multi-Agent Based Microscopic Simulation Modeling for Urban Traffic Flow

Directory of Open Access Journals (Sweden)

Xianyan Kuang

2014-10-01

Full Text Available Traffic simulation plays an important role in the evaluation of traffic decisions. The movement of vehicles essentially is the operating process of drivers, in order to reproduce the urban traffic flow from the micro-aspect on computer, this paper establishes an urban traffic flow microscopic simulation system (UTFSim based on multi-agent. The system is seen as an intelligent virtual environment system (IVES, and the four-layer structure of it is built. The road agent, vehicle agent and signal agent are modeled. The concept of driving trajectory which is divided into LDT (Lane Driving Trajectory and VDDT (Vehicle Dynamic Driving Trajectory is introduced. The “Link-Node” road network model is improved. The driving behaviors including free driving, following driving, lane changing, slowing down, vehicle stop, etc. are analyzed. The results of the signal control experiments utilizing the UTFSim developed in the platform of Visual Studio. NET indicates that it plays a good performance and can be used in the evaluation of traffic management and control.

Solution of partial differential equations by agent-based simulation

International Nuclear Information System (INIS)

Szilagyi, Miklos N

2014-01-01

The purpose of this short note is to demonstrate that partial differential equations can be quickly solved by agent-based simulation with high accuracy. There is no need for the solution of large systems of algebraic equations. This method is especially useful for quick determination of potential distributions and demonstration purposes in teaching electromagnetism. (letters and comments)

An agent-based method for simulating porous fluid-saturated structures with indistinguishable components

Science.gov (United States)

Kashani, Jamal; Pettet, Graeme John; Gu, YuanTong; Zhang, Lihai; Oloyede, Adekunle

2017-10-01

Single-phase porous materials contain multiple components that intermingle up to the ultramicroscopic level. Although the structures of the porous materials have been simulated with agent-based methods, the results of the available methods continue to provide patterns of distinguishable solid and fluid agents which do not represent materials with indistinguishable phases. This paper introduces a new agent (hybrid agent) and category of rules (intra-agent rule) that can be used to create emergent structures that would more accurately represent single-phase structures and materials. The novel hybrid agent carries the characteristics of system's elements and it is capable of changing within itself, while also responding to its neighbours as they also change. As an example, the hybrid agent under one-dimensional cellular automata formalism in a two-dimensional domain is used to generate patterns that demonstrate the striking morphological and characteristic similarities with the porous saturated single-phase structures where each agent of the ;structure; carries semi-permeability property and consists of both fluid and solid in space and at all times. We conclude that the ability of the hybrid agent to change locally provides an enhanced protocol to simulate complex porous structures such as biological tissues which could facilitate models for agent-based techniques and numerical methods.

Analysis of Customer Behaviour and Online Retailers Strategies Using the Agent-Based Simulation

Directory of Open Access Journals (Sweden)

Sava Čavoški

2015-02-01

Full Text Available This paper discusses the application of ABMS – agent-based modelling and simulation in the analysis of customer behaviour on B2C e-commerce websites as well as in the analysis of various business decisions upon the effects of on-line sales. By linking the areas of modelling based on agents and electronic commerce, this paper addresses the new opportunities for a quality assessment of consumer behaviour and reasons explaining this behaviour in e-commerce. The interactions of agents that make up this model are sublimated in the utility function that provides the basis for decision-making in the model. The rules of behaviour and interactions, included in the model through the utility function, denote the complexity of the decision-making process which occurs in evaluation and purchase of products in the part of B2C e-commerce. The simulation model implemented in the software NetLogo enables the monitoring of all interactions between the consumers (ConsumerAgents, seller-Internet sites (SellerAgents and advertisement agents (BannerAgents by generating the indicators of B2C site business performance.

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

Science.gov (United States)

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

Large-scale agent-based social simulation : A study on epidemic prediction and control

NARCIS (Netherlands)

Zhang, M.

2016-01-01

Large-scale agent-based social simulation is gradually proving to be a versatile methodological approach for studying human societies, which could make contributions from policy making in social science, to distributed artificial intelligence and agent technology in computer science, and to theory

A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

Science.gov (United States)

Gu, X.; Blackmore, K. L.

2015-01-01

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation

Science.gov (United States)

Matsuyama, Shinako; Terano, Takao

This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.

Agent-based modeling and simulation of clean heating system adoption in Norway

Energy Technology Data Exchange (ETDEWEB)

Sopha, Bertha Maya

2011-03-15

A sound climate policy encouraging clean energy investment is important to mitigate global warming. Previous research has demonstrated that consumer choice indeed plays an important role in adoption of sustainable technologies. This thesis strives to gain a better understanding of consumers' decision-making on heating systems and to explore the potential application of agent-based modeling (ABM) in exploring mechanism underlying adoption in which heating system adoption by Norwegian households is taken up as a case study. An interdisciplinary approach, applying various established theories including those of psychology, is applied to create a model for consumer behavior and implement this behavior in an Agent-Based Model (ABM) to simulate heating technology diffusion. A mail-survey, carried out in autumn 2008, is a means to collect information for parameterizing the agent-based model, for gaining empirical facts, and for validating the developed model at micro-level. Survey sample consisted of 1500 Norwegian households drawn from population register and 1500 wood pellet users in Norway. The response rates were 10.3% and 34.6% for population sample and wood pellet sample respectively. This study is divided into two parts; empirical analysis and agent-based simulation. The empirical analysis aims at fully understanding the important aspects of adoption decision and their implications, in order to assist simulation. The analysis particularly contributes to the identification of differences/similarities between adopters and non adopters of wood pellet heating with respects to some key points of adoption derived from different theories, psychological factors underlying the adoption-decision of wood pellet heating, and the rationales underlying Norwegian households' decisions regarding their future heating system. The simulation study aims at exploring the mechanism of heterogeneous household decision-making giving rise to the diffusion of heating systems, and

Land-use change arising from rural land exchange : an agent-based simulation model

NARCIS (Netherlands)

Bakker, Martha M.; Alam, Shah Jamal; van Dijk, Jerry|info:eu-repo/dai/nl/29612642X; Rounsevell, Mark D. A.

Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing

Agent-Based Simulation and Assessment of NAS Security and Safety, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The key innovation proposed here is the use of agent-based modeling and simulation to evaluate the safety of the National Airspace under crisis operations and...

Developing an Agent-Based Simulation System for Post-Earthquake Operations in Uncertainty Conditions: A Proposed Method for Collaboration among Agents

Directory of Open Access Journals (Sweden)

Navid Hooshangi

2018-01-01

Full Text Available Agent-based modeling is a promising approach for developing simulation tools for natural hazards in different areas, such as during urban search and rescue (USAR operations. The present study aimed to develop a dynamic agent-based simulation model in post-earthquake USAR operations using geospatial information system and multi agent systems (GIS and MASs, respectively. We also propose an approach for dynamic task allocation and establishing collaboration among agents based on contract net protocol (CNP and interval-based Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS methods, which consider uncertainty in natural hazards information during agents’ decision-making. The decision-making weights were calculated by analytic hierarchy process (AHP. In order to implement the system, earthquake environment was simulated and the damage of the buildings and a number of injuries were calculated in Tehran’s District 3: 23%, 37%, 24% and 16% of buildings were in slight, moderate, extensive and completely vulnerable classes, respectively. The number of injured persons was calculated to be 17,238. Numerical results in 27 scenarios showed that the proposed method is more accurate than the CNP method in the terms of USAR operational time (at least 13% decrease and the number of human fatalities (at least 9% decrease. In interval uncertainty analysis of our proposed simulated system, the lower and upper bounds of uncertain responses are evaluated. The overall results showed that considering uncertainty in task allocation can be a highly advantageous in the disaster environment. Such systems can be used to manage and prepare for natural hazards.

The Simulation of Financial Markets by Agent-Based Mix-Game Models

OpenAIRE

Chengling Gou

2006-01-01

This paper studies the simulation of financial markets using an agent-based mix-game model which is a variant of the minority game (MG). It specifies the spectra of parameters of mix-game models that fit financial markets by investigating the dynamic behaviors of mix-game models under a wide range of parameters. The main findings are (a) in order to approach efficiency, agents in a real financial market must be heterogeneous, boundedly rational and subject to asymmetric information; (b) an ac...

An Agent-Based Simulation for Investigating the Impact of Stereotypes on Task-Oriented Group Formation

Science.gov (United States)

Maghami, Mahsa; Sukthankar, Gita

In this paper, we introduce an agent-based simulation for investigating the impact of social factors on the formation and evolution of task-oriented groups. Task-oriented groups are created explicitly to perform a task, and all members derive benefits from task completion. However, even in cases when all group members act in a way that is locally optimal for task completion, social forces that have mild effects on choice of associates can have a measurable impact on task completion performance. In this paper, we show how our simulation can be used to model the impact of stereotypes on group formation. In our simulation, stereotypes are based on observable features, learned from prior experience, and only affect an agent's link formation preferences. Even without assuming stereotypes affect the agents' willingness or ability to complete tasks, the long-term modifications that stereotypes have on the agents' social network impair the agents' ability to form groups with sufficient diversity of skills, as compared to agents who form links randomly. An interesting finding is that this effect holds even in cases where stereotype preference and skill existence are completely uncorrelated.

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

Science.gov (United States)

Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

2015-09-01

Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

Capacity Analysis for Parallel Runway through Agent-Based Simulation

Directory of Open Access Journals (Sweden)

Yang Peng

2013-01-01

Full Text Available Parallel runway is the mainstream structure of China hub airport, runway is often the bottleneck of an airport, and the evaluation of its capacity is of great importance to airport management. This study outlines a model, multiagent architecture, implementation approach, and software prototype of a simulation system for evaluating runway capacity. Agent Unified Modeling Language (AUML is applied to illustrate the inbound and departing procedure of planes and design the agent-based model. The model is evaluated experimentally, and the quality is studied in comparison with models, created by SIMMOD and Arena. The results seem to be highly efficient, so the method can be applied to parallel runway capacity evaluation and the model propose favorable flexibility and extensibility.

An agent-based simulation model to study accountable care organizations.

Science.gov (United States)

Liu, Pai; Wu, Shinyi

2016-03-01

Creating accountable care organizations (ACOs) has been widely discussed as a strategy to control rapidly rising healthcare costs and improve quality of care; however, building an effective ACO is a complex process involving multiple stakeholders (payers, providers, patients) with their own interests. Also, implementation of an ACO is costly in terms of time and money. Immature design could cause safety hazards. Therefore, there is a need for analytical model-based decision-support tools that can predict the outcomes of different strategies to facilitate ACO design and implementation. In this study, an agent-based simulation model was developed to study ACOs that considers payers, healthcare providers, and patients as agents under the shared saving payment model of care for congestive heart failure (CHF), one of the most expensive causes of sometimes preventable hospitalizations. The agent-based simulation model has identified the critical determinants for the payment model design that can motivate provider behavior changes to achieve maximum financial and quality outcomes of an ACO. The results show nonlinear provider behavior change patterns corresponding to changes in payment model designs. The outcomes vary by providers with different quality or financial priorities, and are most sensitive to the cost-effectiveness of CHF interventions that an ACO implements. This study demonstrates an increasingly important method to construct a healthcare system analytics model that can help inform health policy and healthcare management decisions. The study also points out that the likely success of an ACO is interdependent with payment model design, provider characteristics, and cost and effectiveness of healthcare interventions.

ActivitySim: large-scale agent based activity generation for infrastructure simulation

Energy Technology Data Exchange (ETDEWEB)

Gali, Emmanuel [Los Alamos National Laboratory; Eidenbenz, Stephan [Los Alamos National Laboratory; Mniszewski, Sue [Los Alamos National Laboratory; Cuellar, Leticia [Los Alamos National Laboratory; Teuscher, Christof [PORTLAND STATE UNIV

2008-01-01

The United States' Department of Homeland Security aims to model, simulate, and analyze critical infrastructure and their interdependencies across multiple sectors such as electric power, telecommunications, water distribution, transportation, etc. We introduce ActivitySim, an activity simulator for a population of millions of individual agents each characterized by a set of demographic attributes that is based on US census data. ActivitySim generates daily schedules for each agent that consists of a sequence of activities, such as sleeping, shopping, working etc., each being scheduled at a geographic location, such as businesses or private residences that is appropriate for the activity type and for the personal situation of the agent. ActivitySim has been developed as part of a larger effort to understand the interdependencies among national infrastructure networks and their demand profiles that emerge from the different activities of individuals in baseline scenarios as well as emergency scenarios, such as hurricane evacuations. We present the scalable software engineering principles underlying ActivitySim, the socia-technical modeling paradigms that drive the activity generation, and proof-of-principle results for a scenario in the Twin Cities, MN area of 2.6 M agents.

MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

OpenAIRE

Alexandridis, Konstantinos T.; Pijanowski, Bryan C.

2002-01-01

The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving g...

Pricing and Timing Strategies for New Product Using Agent-Based Simulation of Behavioural Consumers

OpenAIRE

Keeheon Lee; Hoyeop Lee; Chang Ouk Kim

2014-01-01

In this study, we are interested in the problem of determining the pricing and timing strategies of a new product by developing an agent-based product diffusion simulation. In the proposed simulation model, agents imitate behavioural consumers, who are reference dependent and risk averse in the evaluation of new products and whose interactions create word-of-mouth regarding new products. Pricing and timing strategies involve the timing of a new product release, the timing of providing a disco...

Method for distributed agent-based non-expert simulation of manufacturing process behavior

Science.gov (United States)

Ivezic, Nenad; Potok, Thomas E.

2004-11-30

A method for distributed agent based non-expert simulation of manufacturing process behavior on a single-processor computer comprises the steps of: object modeling a manufacturing technique having a plurality of processes; associating a distributed agent with each the process; and, programming each the agent to respond to discrete events corresponding to the manufacturing technique, wherein each discrete event triggers a programmed response. The method can further comprise the step of transmitting the discrete events to each agent in a message loop. In addition, the programming step comprises the step of conditioning each agent to respond to a discrete event selected from the group consisting of a clock tick message, a resources received message, and a request for output production message.

Validation techniques of agent based modelling for geospatial simulations

Directory of Open Access Journals (Sweden)

M. Darvishi

2014-10-01

Full Text Available One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS, biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI’s ArcGIS, OpenMap, GeoTools, etc for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

Validation techniques of agent based modelling for geospatial simulations

Science.gov (United States)

Darvishi, M.; Ahmadi, G.

2014-10-01

One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS), biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI's ArcGIS, OpenMap, GeoTools, etc) for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

An Agent-Based Labor Market Simulation with Endogenous Skill-Demand

Science.gov (United States)

Gemkow, S.

This paper considers an agent-based labor market simulation to examine the influence of skills on wages and unemployment rates. Therefore less and highly skilled workers as well as less and highly productive vacancies are implemented. The skill distribution is exogenous whereas the distribution of the less and highly productive vacancies is endogenous. The different opportunities of the skill groups on the labor market are established by skill requirements. This means that a highly productive vacancy can only be filled by a highly skilled unemployed. Different skill distributions, which can also be interpreted as skill-biased technological change, are simulated by incrementing the skill level of highly skilled persons exogenously. This simulation also provides a microeconomic foundation of the matching function often used in theoretical approaches.

Plan Validation Using DES and Agent-based Simulation

National Research Council Canada - National Science Library

Wong, Teck H; Ong, Kim S

2008-01-01

.... This thesis explores the possibility of using a multi-agent system (MAS) to generate the aggressor's air strike plans, which could be coupled with a low resolution Discrete Event Simulation (DES...

High performance cellular level agent-based simulation with FLAME for the GPU.

Science.gov (United States)

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

Simulation based on intelligent agents of the process of negotiation of the electric power market in Colombia

International Nuclear Information System (INIS)

Pastrana David, Maria Marcela; Guzman Luna, Jaime A; Ovalle Carranza, Demetrio Arturo

2005-01-01

The aim of this paper is describing the phases of analyzing, designing, building and validation of a multi-agent system to simulate the negotiation process of Colombian electric energy market. This project intent to exhibit advantages of multi-agent systems to model simulation processes. Analysis and design phases use MAS-common KADS rnethodology, which is one of the well known for agent-based system modeling. For this purpose, it is modeled the part of negotiation process among market human agents, which is representing by energy buying and selling among energy generators, commercial agents, and consumers

The Simulation of Financial Markets by an Agent-Based Mix-Game Model

OpenAIRE

Chengling Gou

2006-01-01

This paper studies the simulation of financial markets using an agent-based mix-game model which is a variant of the minority game (MG). It specifies the spectra of parameters of mix-game models that fit financial markets by investigating the dynamic behaviors of mix-game models under a wide range of parameters. The main findings are (a) in order to approach efficiency, agents in a real financial market must be heterogeneous, boundedly rational and subject to asymmetric information; (b) an ac...

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

Science.gov (United States)

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

Science.gov (United States)

Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

2014-12-01

Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

A SIMULATION OF CONTRACT FARMING USING AGENT BASED MODELING

Directory of Open Access Journals (Sweden)

Yuanita Handayati

2016-12-01

Full Text Available This study aims to simulate the effects of contract farming and farmer commitment to contract farming on supply chain performance by using agent based modeling as a methodology. Supply chain performance is represented by profits and service levels. The simulation results indicate that farmers should pay attention to customer requirements and plan their agricultural activities in order to fulfill these requirements. Contract farming helps farmers deal with demand and price uncertainties. We also find that farmer commitment is crucial to fulfilling contract requirements. This study contributes to this field from a conceptual as well as a practical point of view. From the conceptual point of view, our simulation results show that different levels of farmer commitment have an impact on farmer performance when implementing contract farming. From a practical point of view, the uncertainty faced by farmers and the market can be managed by implementing cultivation and harvesting scheduling, information sharing, and collective learning as ways of committing to contract farming.

Simulating the Reproductive Behavior of a Region’s Population with an Agent-Based Model

Directory of Open Access Journals (Sweden)

Valeriy Leonidovich Makarov

2015-09-01

Full Text Available The research analyses the impact of the inequality of demographic transition on socio-demographic characteristics of the regional population and on the dynamics of these characteristics. The study was conducted with the help of computer-based experiments (simulations, which was run on the original agent-based model. The model is an artificial society, and personal characteristics of its members are set so that they could represent age-demographic structure of a simulate region. The agents are divided into two subgroups, which differ in their reproductive strategy. The first group has traditional strategy with high birth rate. The second group has considerably lower birth rate, observed in the modern developed societies. The model uses stochastic approaches to imitate the principle processes of population growth: mortality and morbidity. Mortality is set according to age-sex specific mortality coefficients, which do not differ across the population as a whole. New agents (child births appear as a choice of agents – women of reproductive age, and the choice depends on the subgroup. The overall age and social structure of the region is aggregated across individual agents. A number of experiments has been carried out with the model utilization. This allowed forecasting the size and structure of the population of a given region. The results of the experiments have revealed that despite its simplicity, the developed agent-based model well predicts the initial conditions in the region (e.g. age-demographic and social structure. The model shows good fit in terms of estimating the dynamics of major characteristics of the population.

Towards Agent-Based Simulation of Emerging and Large-Scale Social Networks. Examples of the Migrant Crisis and MMORPGs

Directory of Open Access Journals (Sweden)

Schatten, Markus

2016-10-01

Full Text Available Large-scale agent based simulation of social networks is described in the context of the migrant crisis in Syria and the EU as well as massively multi-player on-line role playing games (MMORPG. The recipeWorld system by Terna and Fontana is proposed as a possible solution to simulating large-scale social networks. The initial system has been re-implemented using the Smart Python multi-Agent Development Environment (SPADE and Pyinteractive was used for visualization. We present initial models of simulation that we plan to develop further in future studies. Thus this paper is research in progress that will hopefully establish a novel agent-based modelling system in the context of the ModelMMORPG project.

Simulating Transport and Land Use Interdependencies for Strategic Urban Planning—An Agent Based Modelling Approach

Directory of Open Access Journals (Sweden)

Nam Huynh

2015-10-01

Full Text Available Agent based modelling has been widely accepted as a promising tool for urban planning purposes thanks to its capability to provide sophisticated insights into the social behaviours and the interdependencies that characterise urban systems. In this paper, we report on an agent based model, called TransMob, which explicitly simulates the mutual dynamics between demographic evolution, transport demands, housing needs and the eventual change in the average satisfaction of the residents of an urban area. The ability to reproduce such dynamics is a unique feature that has not been found in many of the like agent based models in the literature. TransMob, is constituted by six major modules: synthetic population, perceived liveability, travel diary assignment, traffic micro-simulator, residential location choice, and travel mode choice. TransMob is used to simulate the dynamics of a metropolitan area in South East of Sydney, Australia, in 2006 and 2011, with demographic evolution. The results are favourably compared against survey data for the area in 2011, therefore validating the capability of TransMob to reproduce the observed complexity of an urban area. We also report on the application of TransMob to simulate various hypothetical scenarios of urban planning policies. We conclude with discussions on current limitations of TransMob, which serve as suggestions for future developments.

Modeling and simulation of virtual human's coordination based on multi-agent systems

Science.gov (United States)

Zhang, Mei; Wen, Jing-Hua; Zhang, Zu-Xuan; Zhang, Jian-Qing

2006-10-01

The difficulties and hotspots researched in current virtual geographic environment (VGE) are sharing space and multiusers operation, distributed coordination and group decision-making. The theories and technologies of MAS provide a brand-new environment for analysis, design and realization of distributed opening system. This paper takes cooperation among virtual human in VGE which multi-user participate in as main researched object. First we describe theory foundation truss of VGE, and present the formalization description of Multi-Agent System (MAS). Then we detailed analyze and research arithmetic of collectivity operating behavior learning of virtual human based on best held Genetic Algorithm(GA), and establish dynamics action model which Multi-Agents and object interact dynamically and colony movement strategy. Finally we design a example which shows how 3 evolutional Agents cooperate to complete the task of colony pushing column box, and design a virtual world prototype of virtual human pushing box collectively based on V-Realm Builder 2.0, moreover we make modeling and dynamic simulation with Simulink 6.

Simulating the influence of life trajectory events on transport mode behavior in an agent-based system

NARCIS (Netherlands)

Verhoeven, M.; Arentze, T.A.; Timmermans, H.J.P.; Waerden, van der P.J.H.J.

2007-01-01

this paper describes the results of a study on the impact of lifecycle or life trajectory events on activity-travel decisions. This lifecycle trajectory of individual agents can be easily incorporated in an agent-based simulation system. This paper focuses on two lifecycle events, change in

Agent-based simulation of electricity markets. A literature review

Energy Technology Data Exchange (ETDEWEB)

Sensfuss, F.; Ragwitz, M. [Fraunhofer-Institut fuer Systemtechnik und Innovationsforschung (ISI), Karlsruhe (Germany); Genoese, M.; Moest, D. [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Industriebetriebslehre und Industrielle Produktion

2007-07-01

Liberalisation, climate policy and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to con-sider issues like market power, bounded rationality of players and the appear-ance of fluctuating energy sources in order to provide adequate legislation. Fur-thermore the interactions between markets and environmental policy instru-ments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets. (orig.)

Perception Modelling of Visitors in Vargas Museum Using Agent-Based Simulation and Visibility Analysis

Science.gov (United States)

Carcellar, B. G., III

2017-10-01

Museum exhibit management is one of the usual undertakings of museum facilitators. Art works must be strategically placed to achieve maximum viewing from the visitors. The positioning of the artworks also highly influences the quality of experience of the visitors. One solution in such problems is to utilize GIS and Agent-Based Modelling (ABM). In ABM, persistent interacting objects are modelled as agents. These agents are given attributes and behaviors that describe their properties as well as their motion. In this study, ABM approach that incorporates GIS is utilized to perform analyticcal assessment on the placement of the artworks in the Vargas Museum. GIS serves as the backbone for the spatial aspect of the simulation such as the placement of the artwork exhibits, as well as possible obstructions to perception such as the columns, walls, and panel boards. Visibility Analysis is also done to the model in GIS to assess the overall visibility of the artworks. The ABM is done using the initial GIS outputs and GAMA, an open source ABM software. Visitors are modelled as agents, moving inside the museum following a specific decision tree. The simulation is done in three use cases: the 10 %, 20 %, and 30 % chance of having a visitor in the next minute. For the case of the said museum, the 10 % chance is determined to be the closest simulation case to the actual and the recommended minimum time to achieve a maximum artwork perception is 1 hour and 40 minutes. Initial assessment of the results shows that even after 3 hours of simulation, small parts of the exhibit show lack of viewers, due to its distance from the entrance. A more detailed decision tree for the visitor agents can be incorporated to have a more realistic simulation.

Technological progress and effects of (supra) regional innovation and production collaboration. An agent-based model simulation study.

NARCIS (Netherlands)

Vermeulen, B.; Pyka, A.; Serguieva, A.; Maringer, D.; Palade, V.; Almeida, R.J.

2014-01-01

We provide a novel technology development model in which economic agents search for transformations to build artifacts. Using this technology development model, we conduct an agent-based model simulation study on the effect of (supra-)regional collaboration in production and innovation on

Simulation of Distance Relay for Load Encroachment Alleviation with Agent Based Supervision of Zone3

Directory of Open Access Journals (Sweden)

Mohamed Badr

2017-03-01

Full Text Available Cascaded tripping of power lines due to mal-operation of zone-3 distance relays has been one of the main causes of many previous blackouts worldwide. Encroachment of load into zone-3 characteristics during stressed system operation conditions is a basic factor for such mal-operation of the relays. By improving the operation of zone-3, it is possible to prevent mal-operations so that cascaded line tripping can be avoided. For proper study of the behavior of distance relay during faults and load encroachment phenomenon, we must build a model of distance relay, so in this paper a modeling study of distance relay is implemented using MATLAB/Simulink program. However, this model is distinguished from previous models that, examines in detail the third zone of distance relay. Many cases are simulated with changing line loading and fault location to ensure the capability of the relay to detect the fault and thus the maximum load ability limit of distance relay is obtained. In order to prevent cascading events caused by hidden failures in zone-3 relays, agent based relay architectures have been suggested in the recent past. In such architectures each zone-3 relay contains agents that require communication with other agents at various relevant relays in order to distinguish a real zone-3 event from a temporary overload. In this paper, a local master agent is consulted by all zone-3 agents before a tripping decision is made. The master agent maintains a rule base which is updated based on the local topology of the network and real time monitoring of the status of other relays and circuit breakers. Cisco Packet Tracer program is used for running communication network simulations. The result of the simulation indicate that the time estimated to send and receive a packet data unit (PDU message between one relay to anther can satisfy the communication requirement for the proposed scheme with fiber media.

Agent-based Modeling Simulation Analysis on the Regulation of Institutional Investor's Encroachment Behavior in Stock Market

Directory of Open Access Journals (Sweden)

Yang Li

2014-05-01

Full Text Available Purpose: This study explores the effective regulation of institutional investor's encroachment behavior in stock market. Given the theoretical and practical importance, the present study examines the effect of the self-adaptive regulation strategy (adjusting the regulation factors such as punishment and the probability of investigating successfully in time for the sake of the small & medium-sized investor protection.Design/methodology/approach: This study was carried out through game theory and agent-based modeling simulation. Firstly, a dynamic game model was built to search the core factors of regulation and the equilibrium paths. Secondly, an agent-based modeling simulation model was built in Swarm to extend the game model. Finally, a simulation experiment (using virtual parameter values was performed to examine the effect of regulation strategy obtained form game model.Findings: The results of this study showed that the core factors of avoiding the institutional investor's encroachment behavior are the punishment and the probability of investigating successfully of the regulator. The core factors embody as the self-adaptability and the capability of regulator. If the regulator can adjust the regulation factors in time, the illegal behaviors will be avoided effectively.Research limitations/implications: The simulation experiment in this paper was performed with virtual parameter values. Although the results of experiment showed the effect of self-adaptive regulation, there are still some differences between simulation experiment and real market situation.Originality/value: The purpose of this study is to investigate an effective regulation strategy of institutional investor's encroachment behavior in stock market in order to maintain market order and protect the benefits of investors. Base on the game model and simulation model, a simulation experiment was preformed and the result showed that the self-adaptive regulation would be effective

Comparing methods of targeting obesity interventions in populations: An agent-based simulation.

Science.gov (United States)

Beheshti, Rahmatollah; Jalalpour, Mehdi; Glass, Thomas A

2017-12-01

Social networks as well as neighborhood environments have been shown to effect obesity-related behaviors including energy intake and physical activity. Accordingly, harnessing social networks to improve targeting of obesity interventions may be promising to the extent this leads to social multiplier effects and wider diffusion of intervention impact on populations. However, the literature evaluating network-based interventions has been inconsistent. Computational methods like agent-based models (ABM) provide researchers with tools to experiment in a simulated environment. We develop an ABM to compare conventional targeting methods (random selection, based on individual obesity risk, and vulnerable areas) with network-based targeting methods. We adapt a previously published and validated model of network diffusion of obesity-related behavior. We then build social networks among agents using a more realistic approach. We calibrate our model first against national-level data. Our results show that network-based targeting may lead to greater population impact. We also present a new targeting method that outperforms other methods in terms of intervention effectiveness at the population level.

Diffusion dynamics and concentration of toxic materials from quantum dots-based nanotechnologies: an agent-based modeling simulation framework

Energy Technology Data Exchange (ETDEWEB)

Agusdinata, Datu Buyung, E-mail: bagusdinata@niu.edu; Amouie, Mahbod [Northern Illinois University, Department of Industrial & Systems Engineering and Environment, Sustainability, & Energy Institute (United States); Xu, Tao [Northern Illinois University, Department of Chemistry and Biochemistry (United States)

2015-01-15

Due to their favorable electrical and optical properties, quantum dots (QDs) nanostructures have found numerous applications including nanomedicine and photovoltaic cells. However, increased future production, use, and disposal of engineered QD products also raise concerns about their potential environmental impacts. The objective of this work is to establish a modeling framework for predicting the diffusion dynamics and concentration of toxic materials released from Trioctylphosphine oxide-capped CdSe. To this end, an agent-based model simulation with reaction kinetics and Brownian motion dynamics was developed. Reaction kinetics is used to model the stability of surface capping agent particularly due to oxidation process. The diffusion of toxic Cd{sup 2+} ions in aquatic environment was simulated using an adapted Brownian motion algorithm. A calibrated parameter to reflect sensitivity to reaction rate is proposed. The model output demonstrates the stochastic spatial distribution of toxic Cd{sup 2+} ions under different values of proxy environmental factor parameters. With the only chemistry considered was oxidation, the simulation was able to replicate Cd{sup 2+} ion release from Thiol-capped QDs in aerated water. The agent-based method is the first to be developed in the QDs application domain. It adds both simplicity of the solubility and rate of release of Cd{sup 2+} ions and complexity of tracking of individual atoms of Cd at the same time.

Diffusion dynamics and concentration of toxic materials from quantum dots-based nanotechnologies: an agent-based modeling simulation framework

International Nuclear Information System (INIS)

Agusdinata, Datu Buyung; Amouie, Mahbod; Xu, Tao

2015-01-01

Due to their favorable electrical and optical properties, quantum dots (QDs) nanostructures have found numerous applications including nanomedicine and photovoltaic cells. However, increased future production, use, and disposal of engineered QD products also raise concerns about their potential environmental impacts. The objective of this work is to establish a modeling framework for predicting the diffusion dynamics and concentration of toxic materials released from Trioctylphosphine oxide-capped CdSe. To this end, an agent-based model simulation with reaction kinetics and Brownian motion dynamics was developed. Reaction kinetics is used to model the stability of surface capping agent particularly due to oxidation process. The diffusion of toxic Cd 2+ ions in aquatic environment was simulated using an adapted Brownian motion algorithm. A calibrated parameter to reflect sensitivity to reaction rate is proposed. The model output demonstrates the stochastic spatial distribution of toxic Cd 2+ ions under different values of proxy environmental factor parameters. With the only chemistry considered was oxidation, the simulation was able to replicate Cd 2+ ion release from Thiol-capped QDs in aerated water. The agent-based method is the first to be developed in the QDs application domain. It adds both simplicity of the solubility and rate of release of Cd 2+ ions and complexity of tracking of individual atoms of Cd at the same time

Validation techniques of agent based modelling for geospatial simulations

OpenAIRE

Darvishi, M.; Ahmadi, G.

2014-01-01

One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent...

An Agent-Based Model of New Venture Creation: Conceptual Design for Simulating Entrepreneurship

Science.gov (United States)

Provance, Mike; Collins, Andrew; Carayannis, Elias

2012-01-01

There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.

Data-driven Travel Demand Modelling and Agent-based Traffic Simulation in Amsterdam Urban Area

NARCIS (Netherlands)

Melnikov, V.R.; Krzhizhanovskaya, V.V.; Lees, M.H.; Boukhanovsky, A.V.

2016-01-01

The goal of this project is the development of a large-scale agent-based traffic simulation system for Amsterdam urban area, validated on sensor data and adjusted for decision support in critical situations and for policy making in sustainable city development, emission control and electric car

Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions

Directory of Open Access Journals (Sweden)

Aloah J Pope

2015-08-01

Full Text Available Interdependencies of ecologic, hydrologic, and social systems challenge traditional approaches to natural resource management in semi-arid regions. As a complex social-ecological system, water demands in the Sonoran Desert from agricultural and urban users often conflicts with water needs for its ecologically-significant riparian corridors. To explore this system, we developed an agent-based model to simulate complex feedbacks between human decisions and environmental conditions in the Rio Sonora Watershed. Cognitive mapping in conjunction with stakeholder participation produced a Bayesian model of conditional probabilities of local human decision-making processes resulting to changes in water demand. Probabilities created in the Bayesian model were incorporated into the agent-based model, so that each agent had a unique probability to make a positive decision based on its perceived environment at each point in time and space. By using a Bayesian approach, uncertainty in the human decision-making process could be incorporated. The spatially-explicit agent-based model simulated changes in depth-to-groundwater by well pumping based on an agent’s water demand. Changes in depth-to-groundwater feedback to influence agent behavior, as well as determine unique vegetation classes within the riparian corridor. Each vegetation class then provides varying stakeholder-defined quality values of ecosystem services. Using this modeling approach allowed us to examine effects on both the ecological and social system of semi-arid riparian corridors under various scenarios. The insight provided by the model contributes to understanding how specific interventions may alter the complex social-ecological system in the future.

Agent-Based Simulation to Support the Effectiveness, Procurement, and Employment of Non-Lethal Weapon Systems

Science.gov (United States)

2017-06-01

INTENTIONALLY LEFT BLANK xv LIST OF ACRONYMS AND ABBREVIATIONS ABS Agent-Based Simulation AQ Al Qaeda CMC Commandant of the Marine Corps DES Discrete -Event...instilling in me the work ethic to accomplish anything I put my mind to. Jake and Jordan, thank you for listening to me complain about math and...used within the DOD, with two of the most common being discrete -event simulation (DES) and ABS. The DOD uses simulation models in support of

Simulating GenCo bidding strategies in electricity markets with an agent-based model

International Nuclear Information System (INIS)

Botterud, Audun; Thimmapuram, Prakash R.; Yamakado, Malo

2005-01-01

In this paper we use an agent-based simulation model, EMCAS, to analyze market power in electricity markets. We focus on the effect of congestion management on the ability of generating companies (GenCos) to raise prices beyond competitive levels. An 11-node test power system is used to compare a market design based on locational marginal pricing with a market design that uses system marginal pricing and congestion management by counter trading. Bidding strategies based on both physical and economic withholding are compared to a base case with production cost bidding. The results show that unilateral market power is exercised under both pricing mechanisms. However, the largest changes in consumer costs and GenCo profits due to strategic bidding occur under the locational marginal pricing scheme. The analysis also illustrates that agent-based modeling can contribute important insights into the complex interactions between the participants in transmission-constrained electricity markets. (Author)

Agent-based simulation in entrepreneurship research

NARCIS (Netherlands)

Yang, S.-J.S.; Chandra, Y.

2009-01-01

Agent-based modeling (ABM) has wide applications in natural and social sciences yet it has not been widely applied in entrepreneurship research. We discuss the nature of ABM, its position among conventional methodologies and then offer a roadmap for developing, testing and extending theories of

Design of a Mobile Agent-Based Adaptive Communication Middleware for Federations of Critical Infrastructure Simulations

Science.gov (United States)

Görbil, Gökçe; Gelenbe, Erol

The simulation of critical infrastructures (CI) can involve the use of diverse domain specific simulators that run on geographically distant sites. These diverse simulators must then be coordinated to run concurrently in order to evaluate the performance of critical infrastructures which influence each other, especially in emergency or resource-critical situations. We therefore describe the design of an adaptive communication middleware that provides reliable and real-time one-to-one and group communications for federations of CI simulators over a wide-area network (WAN). The proposed middleware is composed of mobile agent-based peer-to-peer (P2P) overlays, called virtual networks (VNets), to enable resilient, adaptive and real-time communications over unreliable and dynamic physical networks (PNets). The autonomous software agents comprising the communication middleware monitor their performance and the underlying PNet, and dynamically adapt the P2P overlay and migrate over the PNet in order to optimize communications according to the requirements of the federation and the current conditions of the PNet. Reliable communications is provided via redundancy within the communication middleware and intelligent migration of agents over the PNet. The proposed middleware integrates security methods in order to protect the communication infrastructure against attacks and provide privacy and anonymity to the participants of the federation. Experiments with an initial version of the communication middleware over a real-life networking testbed show that promising improvements can be obtained for unicast and group communications via the agent migration capability of our middleware.

An agent-based simulation model for Clostridium difficile infection control.

Science.gov (United States)

Codella, James; Safdar, Nasia; Heffernan, Rick; Alagoz, Oguzhan

2015-02-01

Control of Clostridium difficile infection (CDI) is an increasingly difficult problem for health care institutions. There are commonly recommended strategies to combat CDI transmission, such as oral vancomycin for CDI treatment, increased hand hygiene with soap and water for health care workers, daily environmental disinfection of infected patient rooms, and contact isolation of diseased patients. However, the efficacy of these strategies, particularly for endemic CDI, has not been well studied. The objective of this research is to develop a valid, agent-based simulation model (ABM) to study C. difficile transmission and control in a midsized hospital. We develop an ABM of a midsized hospital with agents such as patients, health care workers, and visitors. We model the natural progression of CDI in a patient using a Markov chain and the transmission of CDI through agent and environmental interactions. We derive input parameters from aggregate patient data from the 2007-2010 Wisconsin Hospital Association and published medical literature. We define a calibration process, which we use to estimate transition probabilities of the Markov model by comparing simulation results to benchmark values found in published literature. In a comparison of CDI control strategies implemented individually, routine bleach disinfection of CDI-positive patient rooms provides the largest reduction in nosocomial asymptomatic colonization (21.8%) and nosocomial CDIs (42.8%). Additionally, vancomycin treatment provides the largest reduction in relapse CDIs (41.9%), CDI-related mortalities (68.5%), and total patient length of stay (21.6%). We develop a generalized ABM for CDI control that can be customized and further expanded to specific institutions and/or scenarios. Additionally, we estimate transition probabilities for a Markov model of natural CDI progression in a patient through calibration. © The Author(s) 2014.

Agent-Based Simulation of Mass Shootings: Determining How to Limit the Scale of a Tragedy

OpenAIRE

Roy Hayes; Reginald Hayes

2014-01-01

An agent-based simulation was created to examine key parameters in mass shootings. The goal of the simulation was to examine the potential effectiveness of Senator Dianne Feinstein’s (D-Calif.) assault weapons and high-capacity magazines bill. Based on the analysis, the proposed law would have a negligible effect on the number of people shot during mass shootings. The assault weapons portion of the proposed bill will have no effect on the number of people killed or wounded in a mass shootin...

Agent-Based Smart Grid Market Simulation with Connection to Real Infrastructures

DEFF Research Database (Denmark)

Santos, Gabriel; Pinto, Tiago; Gomes, Luis

2015-01-01

The consensus behind Smart Grids (SG) as one of the most promising solutions for the massive integration of renewable energy sources in power systems has led to the practical implementation of several prototypes and pilots that aim at testing and validating SG methodologies. The urgent need...... to accommodate such resources of distributed and intermittent nature and the impact that a deficient management of energy sources has on the global population require that alternative solutions are experimented. This paper presents a multi-agent based SG simulation platform that is connected to physical...

MODELING OF INVESTMENT STRATEGIES IN STOCKS MARKETS: AN APPROACH FROM MULTI AGENT BASED SIMULATION AND FUZZY LOGIC

Directory of Open Access Journals (Sweden)

ALEJANDRO ESCOBAR

2010-01-01

Full Text Available This paper presents a simulation model of a complex system, in this case a financial market, using a MultiAgent Based Simulation approach. Such model takes into account microlevel aspects like the Continuous Double Auction mechanism, which is widely used within stock markets, as well as investor agents reasoning who participate looking for profits. To model such reasoning several variables were considered including general stocks information like profitability and volatility, but also some agent's aspects like their risk tendency. All these variables are incorporated throughout a fuzzy logic approach trying to represent in a faithful manner the kind of reasoning that nonexpert investors have, including a stochastic component in order to model human factors.

Exploring policy options for a transition to sustainable heating system diffusion using an agent-based simulation

International Nuclear Information System (INIS)

Maya Sopha, Bertha; Kloeckner, Christian A.; Hertwich, Edgar G.

2011-01-01

Change in home heating to more efficient and renewable systems is important for a sound climate policy. The present paper aims to identify potential interventions for the uptake of wood-pellet heating in Norway using an agent-based model (ABM). The theoretically based, empirically founded, agent-based simulation demonstrates that financial support, i.e., a stable wood-pellet price, and technical development, i.e., functional reliability improvement, have to be established all at the same time for a successful wood-pellet market to start. Furthermore, a soft intervention through persuading households to use environmentally beneficial heating system is not a promising driver for wood-pellet diffusion. Limitations and suggestions for future work are also discussed. - Research highlights: → The theoretically based, empirically founded, agent-based simulation is applied to investigate potential policy options toward diffusion of wood-pellet heating in Norway. → Relative advantages are necessary for wood-pellet heating to be adopted, consistent with Diffusion of Innovation theory (). → Simultaneous development is also required for further uptake of wood-pellet heating, supporting the existing empirical hypothesis by . → Persuading households to use environmentally friendly heating system is not a promising driver, in line with empirical finding of , who investigated psychological factors underlying the adoption of wood-pellet heating.

Exploring policy options for a transition to sustainable heating system diffusion using an agent-based simulation

Energy Technology Data Exchange (ETDEWEB)

Maya Sopha, Bertha, E-mail: bertha.sopha@ntnu.n [Industrial Ecology Programme and Department of Energy and Process Engineering, Norwegian University of Science and Technology, NO-7491 Trondheim (Norway); Kloeckner, Christian A. [Department of Psychology, Section for Risk Psychology, Environment and Safety (RIPENSA), Norwegian University of Science and Technology, NO-7491 Trondheim (Norway); Hertwich, Edgar G. [Industrial Ecology Programme and Department of Energy and Process Engineering, Norwegian University of Science and Technology, NO-7491 Trondheim (Norway)

2011-05-15

Change in home heating to more efficient and renewable systems is important for a sound climate policy. The present paper aims to identify potential interventions for the uptake of wood-pellet heating in Norway using an agent-based model (ABM). The theoretically based, empirically founded, agent-based simulation demonstrates that financial support, i.e., a stable wood-pellet price, and technical development, i.e., functional reliability improvement, have to be established all at the same time for a successful wood-pellet market to start. Furthermore, a soft intervention through persuading households to use environmentally beneficial heating system is not a promising driver for wood-pellet diffusion. Limitations and suggestions for future work are also discussed. - Research highlights: {yields} The theoretically based, empirically founded, agent-based simulation is applied to investigate potential policy options toward diffusion of wood-pellet heating in Norway. {yields} Relative advantages are necessary for wood-pellet heating to be adopted, consistent with Diffusion of Innovation theory (). {yields} Simultaneous development is also required for further uptake of wood-pellet heating, supporting the existing empirical hypothesis by . {yields} Persuading households to use environmentally friendly heating system is not a promising driver, in line with empirical finding of , who investigated psychological factors underlying the adoption of wood-pellet heating.

On-lattice agent-based simulation of populations of cells within the open-source Chaste framework.

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Figueredo, Grazziela P; Joshi, Tanvi V; Osborne, James M; Byrne, Helen M; Owen, Markus R

2013-04-06

Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the 'what if' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.

On-lattice agent-based simulation of populations of cells within the open-source Chaste framework

KAUST Repository

Figueredo, G. P.

2013-02-21

Over the years, agent-based models have been developed that combine cell division and reinforced random walks of cells on a regular lattice, reaction-diffusion equations for nutrients and growth factors; and ordinary differential equations for the subcellular networks regulating the cell cycle. When linked to a vascular layer, this multiple scale model framework has been applied to tumour growth and therapy. Here, we report on the creation of an agent-based multi-scale environment amalgamating the characteristics of these models within a Virtual Physiological Human (VPH) Exemplar Project. This project enables reuse, integration, expansion and sharing of the model and relevant data. The agent-based and reaction-diffusion parts of the multi-scale model have been implemented and are available for download as part of the latest public release of Chaste (Cancer, Heart and Soft Tissue Environment; http://www.cs.ox.ac.uk/chaste/), part of the VPH Toolkit (http://toolkit.vph-noe.eu/). The environment functionalities are verified against the original models, in addition to extra validation of all aspects of the code. In this work, we present the details of the implementation of the agent-based environment, including the system description, the conceptual model, the development of the simulation model and the processes of verification and validation of the simulation results. We explore the potential use of the environment by presenting exemplar applications of the \\'what if\\' scenarios that can easily be studied in the environment. These examples relate to tumour growth, cellular competition for resources and tumour responses to hypoxia (low oxygen levels). We conclude our work by summarizing the future steps for the expansion of the current system.

Simulating the elimination of sleeping sickness with an agent-based model

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Grébaut Pascal

2016-01-01

Full Text Available Although Human African Trypanosomiasis is largely considered to be in the process of extinction today, the persistence of human and animal reservoirs, as well as the vector, necessitates a laborious elimination process. In this context, modeling could be an effective tool to evaluate the ability of different public health interventions to control the disease. Using the Cormas® system, we developed HATSim, an agent-based model capable of simulating the possible endemic evolutions of sleeping sickness and the ability of National Control Programs to eliminate the disease. This model takes into account the analysis of epidemiological, entomological, and ecological data from field studies conducted during the last decade, making it possible to predict the evolution of the disease within this area over a 5-year span. In this article, we first present HATSim according to the Overview, Design concepts, and Details (ODD protocol that is classically used to describe agent-based models, then, in a second part, we present predictive results concerning the evolution of Human African Trypanosomiasis in the village of Lambi (Cameroon, in order to illustrate the interest of such a tool. Our results are consistent with what was observed in the field by the Cameroonian National Control Program (CNCP. Our simulations also revealed that regular screening can be sufficient, although vector control applied to all areas with human activities could be significantly more efficient. Our results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci.

Serious games experiment toward agent-based simulation

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Wein, Anne; Labiosa, William

2013-01-01

We evaluate the potential for serious games to be used as a scientifically based decision-support product that supports the United States Geological Survey’s (USGS) mission--to provide integrated, unbiased scientific information that can make a substantial contribution to societal well-being for a wide variety of complex environmental challenges. Serious or pedagogical games are an engaging way to educate decisionmakers and stakeholders about environmental challenges that are usefully informed by natural and social scientific information and knowledge and can be designed to promote interactive learning and exploration in the face of large uncertainties, divergent values, and complex situations. We developed two serious games that use challenging environmental-planning issues to demonstrate and investigate the potential contributions of serious games to inform regional-planning decisions. Delta Skelta is a game emulating long-term integrated environmental planning in the Sacramento-San Joaquin Delta, California, that incorporates natural hazards (flooding and earthquakes) and consequences for California water supplies amidst conflicting water interests. Age of Ecology is a game that simulates interactions between economic and ecologic processes, as well as natural hazards while implementing agent-based modeling. The content of these games spans the USGS science mission areas related to water, ecosystems, natural hazards, land use, and climate change. We describe the games, reflect on design and informational aspects, and comment on their potential usefulness. During the process of developing these games, we identified various design trade-offs involving factual information, strategic thinking, game-winning criteria, elements of fun, number and type of players, time horizon, and uncertainty. We evaluate the two games in terms of accomplishments and limitations. Overall, we demonstrated the potential for these games to usefully represent scientific information

Combining integrated river modelling and agent based social simulation for river management; The case study of the Grensmaas project

NARCIS (Netherlands)

Valkering, P.; Krywkow, Jorg; Rotmans, J.; van der Veen, A.; Douben, N.; van Os, A.G.

2003-01-01

In this paper we present a coupled Integrated River Model – Agent Based Social Simulation model (IRM-ABSS) for river management. The models represent the case of the ongoing river engineering project “Grensmaas”. In the ABSS model stakeholders are represented as computer agents negotiating a river

Evolutionary game theory using agent-based methods.

Science.gov (United States)

Adami, Christoph; Schossau, Jory; Hintze, Arend

2016-12-01

Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations. Copyright © 2016 Elsevier B.V. All rights reserved.

New approaches in agent-based modeling of complex financial systems

Science.gov (United States)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Establish an Agent-Simulant Technology Relationship (ASTR)

Science.gov (United States)

2017-04-14

collective protection; CP; decontamination ; decon; contamination avoidance; CA; chemical biological radiological; CBR 16. SECURITY CLASSIFICATION...Within chemical defense, the individual protection (IP), collective protection (CP), decontamination (decon), and contamination avoidance (CA...OT). c. Testing may use chemical warfare agent (CWA), biological warfare agent (BWA), radiological agent, or simulant (surrogate). A simulant is a

Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

Science.gov (United States)

Zhang, Donglan; Giabbanelli, Philippe J; Arah, Onyebuchi A; Zimmerman, Frederick J

2014-07-01

Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

Solving the dial-a-ride problem using agent-based simulation

Directory of Open Access Journals (Sweden)

Campbell, Ian

2016-11-01

Full Text Available The ‘dial-a-ride problem’ (DARP requires a set of customers to be transported by a limited fleet of vehicles between unique origins and destinations under several service constraints, including within defined time windows. The problem is considered NP-hard, and has typically been solved using metaheuristic methods. An agent-based simulation (ABS model was developed, where each vehicle bids to service customers based on a weighted objective function that considers the cost to service the customer and the time quality of the service that would be achieved. The approach applied a pre- processing technique to reduce the search space, given the service time window constraints. Tests of the model showed significantly better customer transit and waiting times than the benchmark datasets. The ABS was able to obtain solutions for much larger problem sizes than the benchmark solutions, with this work being the first known application of ABS to the DARP.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities.

Science.gov (United States)

Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

2016-12-21

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

Directory of Open Access Journals (Sweden)

Ming Liu

2016-12-01

Full Text Available With the development of Machine-to-Machine (M2M technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C, Deployment (D, Resource (R and IOData (IO. Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design.

Semantic Agent-Based Service Middleware and Simulation for Smart Cities

Science.gov (United States)

Liu, Ming; Xu, Yang; Hu, Haixiao; Mohammed, Abdul-Wahid

2016-01-01

With the development of Machine-to-Machine (M2M) technology, a variety of embedded and mobile devices is integrated to interact via the platform of the Internet of Things, especially in the domain of smart cities. One of the primary challenges is that selecting the appropriate services or service combination for upper layer applications is hard, which is due to the absence of a unified semantical service description pattern, as well as the service selection mechanism. In this paper, we define a semantic service representation model from four key properties: Capability (C), Deployment (D), Resource (R) and IOData (IO). Based on this model, an agent-based middleware is built to support semantic service enablement. In this middleware, we present an efficient semantic service discovery and matching approach for a service combination process, which calculates the semantic similarity between services, and a heuristic algorithm to search the service candidates for a specific service request. Based on this design, we propose a simulation of virtual urban fire fighting, and the experimental results manifest the feasibility and efficiency of our design. PMID:28009818

An Immune Agent for Web-Based AI Course

Science.gov (United States)

Gong, Tao; Cai, Zixing

2006-01-01

To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

Application potential of Agent Based Simulation and Discrete Event Simulation in Enterprise integration modelling concepts

Directory of Open Access Journals (Sweden)

Paul-Eric DOSSOU

2013-07-01

Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} This paper aims to present the dilemma of simulation tool selection. Authors discuss the examples of methodologies of enterprises architectures (CIMOSA and GRAI where agent approach is used to solve planning and managing problems. Actually simulation is widely used and practically only one tool which can enable verification of complex systems. Many companies face the problem, which simulation tool is appropriate to use for verification. Selected tools based on ABS and DES are presented. Some tools combining DES and ABS approaches are described. Authors give some recommendation on selection process.

Application potential of Agent Based Simulation and Discrete Event Simulation in Enterprise integration modelling concepts

Directory of Open Access Journals (Sweden)

Pawel PAWLEWSKI

2012-07-01

Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} This paper aims to present the dilemma of simulation tool selection. Authors discuss the examples of methodologies of enterprises architectures (CIMOSA and GRAI where agent approach is used to solve planning and managing problems. Actually simulation is widely used and practically only one tool which can enable verification of complex systems. Many companies face the problem, which simulation tool is appropriate to use for verification. Selected tools based on ABS and DES are presented. Some tools combining DES and ABS approaches are described. Authors give some recommendation on selection process.

An agent-based simulation combined with group decision-making technique for improving the performance of an emergency department

Directory of Open Access Journals (Sweden)

M. Yousefi

Full Text Available This study presents an agent-based simulation modeling in an emergency department. In a traditional approach, a supervisor (or a manager allocates the resources (receptionist, nurses, doctors, etc. to different sections based on personal experience or by using decision-support tools. In this study, each staff agent took part in the process of allocating resources based on their observation in their respective sections, which gave the system the advantage of utilizing all the available human resources during the workday by being allocated to a different section. In this simulation, unlike previous studies, all staff agents took part in the decision-making process to re-allocate the resources in the emergency department. The simulation modeled the behavior of patients, receptionists, triage nurses, emergency room nurses and doctors. Patients were able to decide whether to stay in the system or leave the department at any stage of treatment. In order to evaluate the performance of this approach, 6 different scenarios were introduced. In each scenario, various key performance indicators were investigated before and after applying the group decision-making. The outputs of each simulation were number of deaths, number of patients who leave the emergency department without being attended, length of stay, waiting time and total number of discharged patients from the emergency department. Applying the self-organizing approach in the simulation showed an average of 12.7 and 14.4% decrease in total waiting time and number of patients who left without being seen, respectively. The results showed an average increase of 11.5% in total number of discharged patients from emergency department.

Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

Science.gov (United States)

Gilligan, J. M.; John, N. J.; van der Linden, M.

2015-12-01

Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

Agent-based modelling of cholera diffusion

NARCIS (Netherlands)

Augustijn-Beckers, Petronella; Doldersum, Tom; Useya, Juliana; Augustijn, Dionysius C.M.

2016-01-01

This paper introduces a spatially explicit agent-based simulation model for micro-scale cholera diffusion. The model simulates both an environmental reservoir of naturally occurring V.cholerae bacteria and hyperinfectious V. cholerae. Objective of the research is to test if runoff from open refuse

The application of dynamic micro-simulation model of urban planning based on multi-agent system

Science.gov (United States)

Xu, J.; Shiming, W.

2012-12-01

The dynamic micro-simulation model of urban planning based on multi-agent, is mainly used to measure and predict the impact of the policy on urban land use, employment opportunities and the price of real estate. The representation of the supply and characteristics of land and of real estate development, at a spatial scale. The use of real estate markets as a central organizing focus, with consumer choices and supplier choices explicitly represented, as well as the resulting effects on real estate prices. The relationship of agents to real estate tied to specific locations provided a clean accounting of space and its use. Finally, it will produce a map composited with the dynamic demographic distribution and the dynamic employment transfer by the geographic spatial data. With the data produced by the urban micro-simulation model, it can provide the favorable forecast reference for the scientific urban land use.

Agent Based Modeling Applications for Geosciences

Science.gov (United States)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

Wealth distribution, Pareto law, and stretched exponential decay of money: Computer simulations analysis of agent-based models

Science.gov (United States)

Aydiner, Ekrem; Cherstvy, Andrey G.; Metzler, Ralf

2018-01-01

We study by Monte Carlo simulations a kinetic exchange trading model for both fixed and distributed saving propensities of the agents and rationalize the person and wealth distributions. We show that the newly introduced wealth distribution - that may be more amenable in certain situations - features a different power-law exponent, particularly for distributed saving propensities of the agents. For open agent-based systems, we analyze the person and wealth distributions and find that the presence of trap agents alters their amplitude, leaving however the scaling exponents nearly unaffected. For an open system, we show that the total wealth - for different trap agent densities and saving propensities of the agents - decreases in time according to the classical Kohlrausch-Williams-Watts stretched exponential law. Interestingly, this decay does not depend on the trap agent density, but rather on saving propensities. The system relaxation for fixed and distributed saving schemes are found to be different.

Estimation of Financial Agent-Based Models with Simulated Maximum Likelihood

Czech Academy of Sciences Publication Activity Database

Kukačka, Jiří; Baruník, Jozef

2017-01-01

Roč. 85, č. 1 (2017), s. 21-45 ISSN 0165-1889 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : heterogeneous agent model, * simulated maximum likelihood * switching Subject RIV: AH - Economics OBOR OECD: Finance Impact factor: 1.000, year: 2016 http://library.utia.cas.cz/separaty/2017/E/kukacka-0478481.pdf

Evaluation of wholesale electric power market rules and financial risk management by agent-based simulations

Science.gov (United States)

Yu, Nanpeng

As U.S. regional electricity markets continue to refine their market structures, designs and rules of operation in various ways, two critical issues are emerging. First, although much experience has been gained and costly and valuable lessons have been learned, there is still a lack of a systematic platform for evaluation of the impact of a new market design from both engineering and economic points of view. Second, the transition from a monopoly paradigm characterized by a guaranteed rate of return to a competitive market created various unfamiliar financial risks for various market participants, especially for the Investor Owned Utilities (IOUs) and Independent Power Producers (IPPs). This dissertation uses agent-based simulation methods to tackle the market rules evaluation and financial risk management problems. The California energy crisis in 2000-01 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This dissertation presents a flexible and integrative method to assess market designs through agent-based simulations. Realistic simulation scenarios on a 225-bus system are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GenCo) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. The importance of financial risk management is exemplified by the recent financial crisis. In this

Using an Agent-Based Modeling Simulation and Game to Teach Socio-Scientific Topics

Directory of Open Access Journals (Sweden)

Lori L. Scarlatos

2014-02-01

Full Text Available In our modern world, where science, technology and society are tightly interwoven, it is essential that all students be able to evaluate scientific evidence and make informed decisions. Energy Choices, an agent-based simulation with a multiplayer game interface, was developed as a learning tool that models the interdependencies between the energy choices that are made, growth in local economies, and climate change on a global scale. This paper presents the results of pilot testing Energy Choices in two different settings, using two different modes of delivery.

On the formal analysis of the dynamics of simulated agent societies

NARCIS (Netherlands)

Popova, V.; Eiben, A.E.; Jonker, C.M.; Schut, M.C.

2007-01-01

To analyze emergent behavior, a formal framework is needed to characterize the structure and dynamics of complex interaction-based multi-agent systems. We introduce an extension of an existing agent testbed for artificial societies making it possible to formally analyze the dynamics of the simulated

Using the Integration of Discrete Event and Agent-Based Simulation to Enhance Outpatient Service Quality in an Orthopedic Department

Directory of Open Access Journals (Sweden)

Cholada Kittipittayakorn

2016-01-01

Full Text Available Many hospitals are currently paying more attention to patient satisfaction since it is an important service quality index. Many Asian countries’ healthcare systems have a mixed-type registration, accepting both walk-in patients and scheduled patients. This complex registration system causes a long patient waiting time in outpatient clinics. Different approaches have been proposed to reduce the waiting time. This study uses the integration of discrete event simulation (DES and agent-based simulation (ABS to improve patient waiting time and is the first attempt to apply this approach to solve this key problem faced by orthopedic departments. From the data collected, patient behaviors are modeled and incorporated into a massive agent-based simulation. The proposed approach is an aid for analyzing and modifying orthopedic department processes, allows us to consider far more details, and provides more reliable results. After applying the proposed approach, the total waiting time of the orthopedic department fell from 1246.39 minutes to 847.21 minutes. Thus, using the correct simulation model significantly reduces patient waiting time in an orthopedic department.

Using the Integration of Discrete Event and Agent-Based Simulation to Enhance Outpatient Service Quality in an Orthopedic Department.

Science.gov (United States)

Kittipittayakorn, Cholada; Ying, Kuo-Ching

2016-01-01

Many hospitals are currently paying more attention to patient satisfaction since it is an important service quality index. Many Asian countries' healthcare systems have a mixed-type registration, accepting both walk-in patients and scheduled patients. This complex registration system causes a long patient waiting time in outpatient clinics. Different approaches have been proposed to reduce the waiting time. This study uses the integration of discrete event simulation (DES) and agent-based simulation (ABS) to improve patient waiting time and is the first attempt to apply this approach to solve this key problem faced by orthopedic departments. From the data collected, patient behaviors are modeled and incorporated into a massive agent-based simulation. The proposed approach is an aid for analyzing and modifying orthopedic department processes, allows us to consider far more details, and provides more reliable results. After applying the proposed approach, the total waiting time of the orthopedic department fell from 1246.39 minutes to 847.21 minutes. Thus, using the correct simulation model significantly reduces patient waiting time in an orthopedic department.

Agent-based simulation in management and organizational studies: a survey

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Nelson Alfonso Gómez-Cruz

2017-10-01

Full Text Available Purpose - The purpose of this paper is to provide a comprehensive survey of the literature about the use of agent-based simulation (ABS in the study of organizational behavior, decision making, and problem-solving. It aims at contributing to the consolidation of ABS as a field of applied research in management and organizational studies. Design/methodology/approach - The authors carried out a non-systematic search in literature published between 2000 and 2016, by using the keyword “agent-based” to search through Scopus’ business, management and accounting database. Additional search criteria were devised using the papers’ keywords and the categories defined by the divisions and interest groups of the Academy of Management. The authors found 181 articles for this survey. Findings - The survey shows that ABS provides a robust and rigorous framework to elaborate descriptions, explanations, predictions and theories about organizations and their processes as well as develop tools that support strategic and operational decision making and problem-solving. The authors show that the areas that report the highest number of applications are operations and logistics (37 percent, marketing (17 percent and organizational behavior (14 percent. Originality/value - The paper illustrates the increasingly prominent role of ABS in fields such as organizational behavior, strategy, human resources, marketing and logistics. To-date, this is the most complete survey about ABS in all management areas.

Designing Citizen Business Loan Model to Reduce Non-Performing Loan: An Agent-based Modeling and Simulation Approach in Regional Development

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Moses L Singgih

2015-09-01

Full Text Available Citizen Business Loan (CBL constitutes a program poverty alleviation based on economic empowerment of small and medium enterprise. This study focuses on implementation of CBL at Regional Development Bank branch X. The problem is the existing of interdependencies between CBL’s implements (Bank and the uncertainty of debtor’s capability in returning the credit. The impact of this circumstance is non-performing loan (NPL becomes relatively high (22%. The ultimate objective is to minimize NPL by designing the model based on the agent that can represent the problem through a simulation using agent-based modeling and simulation (ABMS. The model is considered by managing the probability of the debtor to pay or not based on 5 C categories, they are: character, capacity, capital, condition, and collateral that inherent to each debtor. There are two improvement scenarios proposed in this model. The first scenario only involves the first category of debtor in simulation. The result of this scenario is NPL value as 0%. The second scenario includes the first and second of debtor’s category in simulation and resulting NPL value between 4.6% and 11.4%.

R&D networks and regional knowledge production: an agent-based simulation of the Austrian competence centres programme

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Manuela Korber

2014-06-01

Full Text Available Publicly funded competence centres have gained high recognition for improving science-industry collaboration. With the requirement for long-term and geographically concentrated R&D, competence centres provide an environment for joint learning and transfer of “sticky” knowledge. The objective of this paper is to investigate how a competence centres programme affects knowledge production in the regional innovation system. In order to address this issue, we draw on a simulation approach and develop an agent-based model of the Vienna Life Sciences innovation system. Companies, research organisations and universities are heterogeneous agents that create scientific publications, patents, as well as high-tech jobs. Simulation runs refer to long-term scenarios regarding the level and duration of public funding. By addressing the complexities of knowledge interaction in the context of the “local buzz” versus “global pipelines” discussion, the results show the potential of empirically calibrated simulation models for ex-ante impact assessment in R&D policy.

The Multi-Agent Transport Simulation MATSim

OpenAIRE

Horni Andreas; Nagel Kai; Axhausen Kay W.

2016-01-01

"The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. T...

A water market simulator considering pair-wise trades between agents

Science.gov (United States)

Huskova, I.; Erfani, T.; Harou, J. J.

2012-04-01

In many basins in England no further water abstraction licences are available. Trading water between water rights holders has been recognized as a potentially effective and economically efficient strategy to mitigate increasing scarcity. A screening tool that could assess the potential for trade through realistic simulation of individual water rights holders would help assess the solution's potential contribution to local water management. We propose an optimisation-driven water market simulator that predicts pair-wise trade in a catchment and represents its interaction with natural hydrology and engineered infrastructure. A model is used to emulate licence-holders' willingness to engage in short-term trade transactions. In their simplest form agents are represented using an economic benefit function. The working hypothesis is that trading behaviour can be partially predicted based on differences in marginal values of water over space and time and estimates of transaction costs on pair-wise trades. We discuss the further possibility of embedding rules, norms and preferences of the different water user sectors to more realistically represent the behaviours, motives and constraints of individual licence holders. The potential benefits and limitations of such a social simulation (agent-based) approach is contrasted with our simulator where agents are driven by economic optimization. A case study based on the Dove River Basin (UK) demonstrates model inputs and outputs. The ability of the model to suggest impacts of water rights policy reforms on trading is discussed.

Applying GIS and high performance agent-based simulation for managing an Old World Screwworm fly invasion of Australia.

Science.gov (United States)

Welch, M C; Kwan, P W; Sajeev, A S M

2014-10-01

Agent-based modelling has proven to be a promising approach for developing rich simulations for complex phenomena that provide decision support functions across a broad range of areas including biological, social and agricultural sciences. This paper demonstrates how high performance computing technologies, namely General-Purpose Computing on Graphics Processing Units (GPGPU), and commercial Geographic Information Systems (GIS) can be applied to develop a national scale, agent-based simulation of an incursion of Old World Screwworm fly (OWS fly) into the Australian mainland. The development of this simulation model leverages the combination of massively data-parallel processing capabilities supported by NVidia's Compute Unified Device Architecture (CUDA) and the advanced spatial visualisation capabilities of GIS. These technologies have enabled the implementation of an individual-based, stochastic lifecycle and dispersal algorithm for the OWS fly invasion. The simulation model draws upon a wide range of biological data as input to stochastically determine the reproduction and survival of the OWS fly through the different stages of its lifecycle and dispersal of gravid females. Through this model, a highly efficient computational platform has been developed for studying the effectiveness of control and mitigation strategies and their associated economic impact on livestock industries can be materialised. Copyright © 2014 International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.

Modelling and Simulating Complex Systems in Biology: introducing NetBioDyn : A Pedagogical and Intuitive Agent-Based Software

OpenAIRE

Ballet, Pascal; Rivière, Jérémy; Pothet, Alain; Théron, Michaël; Pichavant, Karine; Abautret, Frank; Fronville, Alexandra; Rodin, Vincent

2017-01-01

International audience; Modelling and teaching complex biological systems is a difficult process. Multi-Agent Based Simulations (MABS) have proved to be an appropriate approach both in research and education when dealing with such systems including emergent, self-organizing phenomena. This chapter presents NetBioDyn, an original software aimed at biologists (students, teachers, researchers) to easily build and simulate complex biological mechanisms observed in multicellular and molecular syst...

Agent-Based Simulation of School Choice in Bandung, Indonesia: The Emergence of Enrolment Pattern Trough Individual Preferences

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Dhanan Sarwo Utomo

2012-01-01

Full Text Available This study is motivated by the reality that school choice programs that is currently implemented in Bandung that, always resulting student deficit (lack of student in some schools. In this study, a mechanism that can describe how the enrollment pattern in a school choice program emerge as a result of individual preferences of the prospective students, is constructed. Using computer simulation, virtual experiments are conducted. In these experiments, the enrollment patterns and the number of student deficit that were resulted by various school choice program configurations are analyzed. Based on the experiment results, modification of the current program that can minimize the number of student deficit can be purposed.Keywords: agent-based simulation, school choice, computer simulation

A Multi-Agent Traffic Control Model Based on Distributed System

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Qian WU

2014-06-01

Full Text Available With the development of urbanization construction, urban travel has become a quite thorny and imminent problem. Some previous researches on the large urban traffic systems easily change into NPC problems. We purpose a multi-agent inductive control model based on the distributed approach. To describe the real traffic scene, this model designs four different types of intelligent agents, i.e. we regard each lane, route, intersection and traffic region as different types of intelligent agents. Each agent can achieve the real-time traffic data from its neighbor agents, and decision-making agents establish real-time traffic signal plans through the communication between local agents and their neighbor agents. To evaluate the traffic system, this paper takes the average delay, the stopped time and the average speed as performance parameters. Finally, the distributed multi-agent is simulated on the VISSIM simulation platform, the simulation results show that the multi-agent system is more effective than the adaptive control system in solving the traffic congestion.

Enhancing Transportation Education through On-line Simulation using an Agent-Based Demand and Assignment Model

OpenAIRE

Shanjiang Zhu; Feng Xie; David Levinson

2005-01-01

This research explores the effectiveness of using simulation as a tool for enhancing classroom learning in the Civil Engineering Department of the University of Minnesota at Twin Cities. The authors developed a modern transportation planning software package, Agent-based Demand and Assignment Model (ADAM), that is consistent with our present understanding of travel behavior, that is platform independent, and that is easy to learn and is thus usable by students. An in-class project incorporate...

ABS-TrustSDN: An Agent-Based Simulator of Trust Strategies in Software-Defined Networks

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Iván García-Magariño

2017-01-01

Full Text Available Software-defined networks (SDNs have become a mechanism to separate the control plane and the data plane in the communication in networks. SDNs involve several challenges around their security and their confidentiality. Ideally, SDNs should incorporate autonomous and adaptive systems for controlling the routing to be able to isolate network resources that may be malfunctioning or whose security has been compromised with malware. The current work introduces a novel agent-based framework that simulates SDN isolation protocols by means of trust and reputation models. This way, SDN programmers may estimate the repercussions of certain isolation protocols based on trust models before actually deploying the protocol into the network.

Agent-Based Simulations for Project Management

Science.gov (United States)

White, J. Chris; Sholtes, Robert M.

2011-01-01

Currently, the most common approach used in project planning tools is the Critical Path Method (CPM). While this method was a great improvement over the basic Gantt chart technique being used at the time, it now suffers from three primary flaws: (1) task duration is an input, (2) productivity impacts are not considered , and (3) management corrective actions are not included. Today, computers have exceptional computational power to handle complex simulations of task e)(eculion and project management activities (e.g ., dynamically changing the number of resources assigned to a task when it is behind schedule). Through research under a Department of Defense contract, the author and the ViaSim team have developed a project simulation tool that enables more realistic cost and schedule estimates by using a resource-based model that literally turns the current duration-based CPM approach "on its head." The approach represents a fundamental paradigm shift in estimating projects, managing schedules, and reducing risk through innovative predictive techniques.

Agent-based Modeling with MATSim for Hazards Evacuation Planning

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Jones, J. M.; Ng, P.; Henry, K.; Peters, J.; Wood, N. J.

2015-12-01

Hazard evacuation planning requires robust modeling tools and techniques, such as least cost distance or agent-based modeling, to gain an understanding of a community's potential to reach safety before event (e.g. tsunami) arrival. Least cost distance modeling provides a static view of the evacuation landscape with an estimate of travel times to safety from each location in the hazard space. With this information, practitioners can assess a community's overall ability for timely evacuation. More information may be needed if evacuee congestion creates bottlenecks in the flow patterns. Dynamic movement patterns are best explored with agent-based models that simulate movement of and interaction between individual agents as evacuees through the hazard space, reacting to potential congestion areas along the evacuation route. The multi-agent transport simulation model MATSim is an agent-based modeling framework that can be applied to hazard evacuation planning. Developed jointly by universities in Switzerland and Germany, MATSim is open-source software written in Java and freely available for modification or enhancement. We successfully used MATSim to illustrate tsunami evacuation challenges in two island communities in California, USA, that are impacted by limited escape routes. However, working with MATSim's data preparation, simulation, and visualization modules in an integrated development environment requires a significant investment of time to develop the software expertise to link the modules and run a simulation. To facilitate our evacuation research, we packaged the MATSim modules into a single application tailored to the needs of the hazards community. By exposing the modeling parameters of interest to researchers in an intuitive user interface and hiding the software complexities, we bring agent-based modeling closer to practitioners and provide access to the powerful visual and analytic information that this modeling can provide.

The Dynamic Optimization of the Departure Times of Metro Users during Rush Hour in an Agent-Based Simulation: A Case Study in Shenzhen, China

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Yuliang Xi

2017-10-01

Full Text Available As serious traffic problems have increased throughout the world, various types of studies, especially traffic simulations, have been conducted to investigate this issue. Activity-based traffic simulation models, such as MATSim (Multi-Agent Transport Simulation, are intended to identify optimal combinations of activities in time and space. It is also necessary to examine commuting-based traffic simulations. Such simulations focus on optimizing travel times by adjusting departure times, travel modes or travel routes to present travel suggestions to the public. This paper examines the optimal departure times of metro users during rush hour using a newly developed simulation tool. A strategy for identifying relatively optimal departure times is identified. This study examines 103,637 person agents (passengers in Shenzhen, China, and reports their average departure time, travel time and travel utility, as well as the numbers of person agents who are late and miss metro trips in every iteration. The results demonstrate that as the number of iterations increases, the average travel time of these person agents decreases by approximately 4 min. Moreover, the latest average departure time with no risk of being late when going to work is approximately 8:04, and the earliest average departure time with no risk of missing metro trips when getting off work is approximately 17:50.

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

Science.gov (United States)

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

Agent-based models in economics a toolkit

CERN Document Server

Fagiolo, Giorgio; Gallegati, Mauro; Richiardi, Matteo; Russo, Alberto

2018-01-01

In contrast to mainstream economics, complexity theory conceives the economy as a complex system of heterogeneous interacting agents characterised by limited information and bounded rationality. Agent Based Models (ABMs) are the analytical and computational tools developed by the proponents of this emerging methodology. Aimed at students and scholars of contemporary economics, this book includes a comprehensive toolkit for agent-based computational economics, now quickly becoming the new way to study evolving economic systems. Leading scholars in the field explain how ABMs can be applied fruitfully to many real-world economic examples and represent a great advancement over mainstream approaches. The essays discuss the methodological bases of agent-based approaches and demonstrate step-by-step how to build, simulate and analyse ABMs and how to validate their outputs empirically using the data. They also present a wide set of applications of these models to key economic topics, including the business cycle, lab...

An Empirical Agent-Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework.

Science.gov (United States)

Kandiah, Venu; Binder, Andrew R; Berglund, Emily Z

2017-10-01

Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large-scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision-making process. Based on the social amplification of risk framework, our agent-based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the "risk publics" model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community-level parameters-including social groups, relationships, and communication variables, also from survey data-are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks. © 2017 Society for Risk Analysis.

Data Provenance for Agent-Based Models in a Distributed Memory

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Delmar B. Davis

2018-04-01

Full Text Available Agent-Based Models (ABMs assist with studying emergent collective behavior of individual entities in social, biological, economic, network, and physical systems. Data provenance can support ABM by explaining individual agent behavior. However, there is no provenance support for ABMs in a distributed setting. The Multi-Agent Spatial Simulation (MASS library provides a framework for simulating ABMs at fine granularity, where agents and spatial data are shared application resources in a distributed memory. We introduce a novel approach to capture ABM provenance in a distributed memory, called ProvMASS. We evaluate our technique with traditional data provenance queries and performance measures. Our results indicate that a configurable approach can capture provenance that explains coordination of distributed shared resources, simulation logic, and agent behavior while limiting performance overhead. We also show the ability to support practical analyses (e.g., agent tracking and storage requirements for different capture configurations.

Evolutionary Agent-Based Simulation of the Introduction of New Technologies in Air Traffic Management

Science.gov (United States)

Yliniemi, Logan; Agogino, Adrian K.; Tumer, Kagan

2014-01-01

Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.

Simulating Spatial Growth Patterns in Developing Countries: an Agent Based Modelling Approach. A Case of Shama in the Western Region of Ghana

Science.gov (United States)

Inkoom, J. N.

2011-12-01

In Sub-Saharan Africa, rapid urban growth is characterized by prolific expansion of unplanned (informal) structures, and unguided spatial expansion. These unguided expansions by human agents have outstripped the regulatory capacities of Central and Local government. Governmental institutions in finding solutions to the unguided expansion in unplanned use of land have to call for the modelling of what influences the spatial decision and role of human agents in the growth of informal settlement. The objective of the study is to simulate spatial growth pattern of settlements in the Shama district using an agent based model. The study was conducted within a framework of NetLogo. The NetLogo assisted to incorporate and simulate driving forces that affect location decision-making by households and the growth of informal settlement. A survey was conducted to obtain household location decision preferences. The development of unplanned settlement has been a function of land price, proximity to economic centre's, household economic potential, and the location decision-making patterns of households. The exploratory analysis found particularly that majority of spontaneous development took place on areas liable to floods suggesting that some structures fall outside the required building regulations. The application of the proposed model indicates its potential to improve urban planning policies and decision-making processes in emerging cities of developing countries. Also, the result of the simulation suggests potential preferential location for residential development. The research justifies an approach in the area of simulating urban dynamics with agent-based models.

A hybrid agent-based approach for modeling microbiological systems.

Science.gov (United States)

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Multi-agent simulation of the von Thunen model formation mechanism

Science.gov (United States)

Tao, Haiyan; Li, Xia; Chen, Xiaoxiang; Deng, Chengbin

2008-10-01

This research tries to explain the internal driving forces of circular structure formation in urban geography via the simulation of interaction between individual behavior and market. On the premise of single city center, unchanged scale merit and complete competition, enterprise migration theory as well, an R-D algorithm, that has agents searched the best behavior rules in some given locations, is introduced with agent-based modeling technique. The experiment conducts a simulation on Swarm platform, whose result reflects and replays the formation process of Von Thünen circular structure. Introducing and considering some heterogeneous factors, such as traffic roads, the research verifies several landuse models and discusses the self-adjustment function of price mechanism.

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

Science.gov (United States)

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472

Application of Transaction Costs in Analyzing Transport Corridors Using Multi-Agent-Based Simulation

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Lawrence E. Henesey

2006-03-01

Full Text Available In analyzing the freight transportation systems, such as thetransport of intermodal containers, often direct monetary costsassociated with transportation are used to evaluate or determinethe choice of transport corridor. In forming decisions ontransport co"idor choice, this paper proposes that transactioncosts can be considered as an additional determinant in conductingtransport corridor analysis. The application of transactioncosts theory in analyzing the organizations and the transactionsthat occur, assists in indicating as to which governancestructure results in higher efficiencies. Efficiency is seen as eitherthe minimisation on costs or the maximisation of customerservice levels. The use of multi-agent based simulation for modellingthe organisational structure and mechanisms provides anovel approach in understanding the relationships in a regionaltransport co"idor.

Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

Science.gov (United States)

Tučník, Petr; Bureš, Vladimír

2016-01-01

Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

A technology path to tactical agent-based modeling

Science.gov (United States)

James, Alex; Hanratty, Timothy P.

2017-05-01

Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

Agent 2003 Conference on Challenges in Social Simulation

Energy Technology Data Exchange (ETDEWEB)

Margaret Clemmons, ed.

2003-01-01

Welcome to the Proceedings of the fourth in a series of agent simulation conferences cosponsored by Argonne National Laboratory and The University of Chicago. Agent 2003 is the second conference in which three Special Interest Groups from the North American Association for Computational Social and Organizational Science (NAACSOS) have been involved in planning the program--Computational Social Theory; Simulation Applications; and Methods, Toolkits and Techniques. The theme of Agent 2003, Challenges in Social Simulation, is especially relevant, as there seems to be no shortage of such challenges. Agent simulation has been applied with increasing frequency to social domains for several decades, and its promise is clear and increasingly visible. Like any nascent scientific methodology, however, it faces a number of problems or issues that must be addressed in order to progress. These challenges include: (1) Validating models relative to the social settings they are designed to represent; (2) Developing agents and interactions simple enough to understand but sufficiently complex to do justice to the social processes of interest; (3) Bridging the gap between empirically spare artificial societies and naturally occurring social phenomena; (4) Building multi-level models that span processes across domains; (5) Promoting a dialog among theoretical, qualitative, and empirical social scientists and area experts, on the one hand, and mathematical and computational modelers and engineers, on the other; (6) Using that dialog to facilitate substantive progress in the social sciences; and (7) Fulfilling the aspirations of users in business, government, and other application areas, while recognizing and addressing the preceding challenges. Although this list hardly exhausts the challenges the field faces, it does identify topics addressed throughout the presentations of Agent 2003. Agent 2003 is part of a much larger process in which new methods and techniques are applied to

Agent-Based Collaborative Traffic Flow Management, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We propose agent-based game-theoretic approaches for simulation of strategies involved in multi-objective collaborative traffic flow management (CTFM). Intelligent...

Modelling and simulation of electrical energy systems through a complex systems approach using agent-based models

Energy Technology Data Exchange (ETDEWEB)

Kremers, Enrique

2013-10-01

Complexity science aims to better understand the processes of both natural and man-made systems which are composed of many interacting entities at different scales. A disaggregated approach is proposed for simulating electricity systems, by using agent-based models coupled to continuous ones. The approach can help in acquiring a better understanding of the operation of the system itself, e.g. on emergent phenomena or scale effects; as well as in the improvement and design of future smart grids.

Non-infectious plasmid engineered to simulate multiple viral threat agents.

Science.gov (United States)

Carrera, Monica; Sagripanti, Jose-Luis

2009-07-01

The aim of this study was to design and construct a non-virulent simulant to replace several pathogenic viruses in the development of detection and identification methods in biodefense. A non-infectious simulant was designed and engineered to include the nucleic acid signature of VEEV (Venezuelan Equine Encephalitis virus), Influenza virus, Rift Valley Fever virus, Machupo virus, Lassa virus, Yellow Fever virus, Ebola virus, Eastern Equine Encephalitis virus, Junin virus, Marburg virus, Dengue virus, and Crimean-Congo virus, all in a single construct. The nucleic acid sequences of all isolates available for each virus species were aligned using ClustalW software in order to obtain conserved regions of the viral genomes. Specific primers were designed to permit the identification and differentiation between viral threat agents. A chimera of 3143 base pairs was engineered to produce 13 PCR amplicons of different sizes. PCR amplification of the simulant with virus-specific primers revealed products of the predicted length, in bands of similar intensity, and without detectable unspecific products by electrophoresis analysis. The simulant described could reduce the need to use infectious viruses in the development of detection and diagnostic methods, and could also be useful as a non-virulent positive control in nucleic acid-based tests against biological threat agents.

Agent-Based Modeling: A Powerful Tool for Tourism Researchers

NARCIS (Netherlands)

Nicholls, Sarah; Amelung, B.; Student, Jillian

2017-01-01

Agent-based modeling (ABM) is a way of representing complex systems of autonomous agents or actors, and of simulating the multiple potential outcomes of these agents’ behaviors and interactions in the form of a range of alternatives or futures. Despite the complexity of the tourism system, and the

A framework for service enterprise workflow simulation with multi-agents cooperation

Science.gov (United States)

Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun

2013-11-01

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.

Modelling and Simulating of Risk Behaviours in Virtual Environments Based on Multi-Agent and Fuzzy Logic

Directory of Open Access Journals (Sweden)

Linqin Cai

2013-11-01

Full Text Available Due to safety and ethical issues, traditional experimental approaches to modelling underground risk behaviours can be costly, dangerous and even impossible to realize. Based on multi-agent technology, a virtual coalmine platform for risk behaviour simulation is presented to model and simulate the human-machine-environment related risk factors in underground coalmines. To reveal mine workers' risk behaviours, a fuzzy emotional behaviour model is proposed to simulate underground miners' responding behaviours to potential hazardous events based on cognitive appraisal theories and fuzzy logic techniques. The proposed emotion model can generate more believable behaviours for virtual miners according to personalized emotion states, internal motivation needs and behaviour selection thresholds. Finally, typical accident cases of underground hazard spotting and locomotive transport were implemented. The behaviour believability of virtual miners was evaluated with a user assessment method. Experimental results show that the proposed models can create more realistic and reasonable behaviours in virtual coalmine environments, which can improve miners' risk awareness and further train miners' emergent decision-making ability when facing unexpected underground situations.

Impact of Carbon Quota Allocation Mechanism on Emissions Trading: An Agent-Based Simulation

Directory of Open Access Journals (Sweden)

Wei Jiang

2016-08-01

Full Text Available This paper establishes an agent-based simulation system of the carbon emissions trading in accordance with the complex feature of the trading process. This system analyzes the impact of the carbon quota allocation mechanism on emissions trading for three different aspects including the amount of emissions reduction, the economic effect on the emitters, and the emissions reduction cost. Based on the data of the carbon emissions of different industries in China, several simulations were made. The results indicate that the emissions trading policy can effectively reduce carbon emissions in a perfectly competitive market. Moreover, by comparing separate quota allocation mechanisms, we obtain the result that the scheme with a small extent quota decrease in a comprehensive allocation mechanism can minimize the unit carbon emission cost. Implementing this scheme can also achieve minimal effects of carbon emissions limitation on the economy on the basis that the environment is not destroyed. However, excessive quota decrease cannot promote the emitters to reduce emission. Taking into account that several developing countries have the dual task of limiting carbon emissions and developing the economy, it is necessary to adopt a comprehensive allocation mechanism of the carbon quota and increase the initial proportion of free allocation.

An agent-based simulation of power generation company behavior in electricity markets under different market-clearing mechanisms

International Nuclear Information System (INIS)

Aliabadi, Danial Esmaeili; Kaya, Murat; Şahin, Güvenç

2017-01-01

Deregulated electricity markets are expected to provide affordable electricity for consumers through promoting competition. Yet, the results do not always fulfill the expectations. The regulator's market-clearing mechanism is a strategic choice that may affect the level of competition in the market. We conceive of the market-clearing mechanism as composed of two components: pricing rules and rationing policies. We investigate the strategic behavior of power generation companies under different market-clearing mechanisms using an agent-based simulation model which integrates a game-theoretical understanding of the auction mechanism in the electricity market and generation companies' learning mechanism. Results of our simulation experiments are presented using various case studies representing different market settings. The market in simulations is observed to converge to a Nash equilibrium of the stage game or to a similar state under most parameter combinations. Compared to pay-as-bid pricing, bid prices are closer to marginal costs on average under uniform pricing while GenCos' total profit is also higher. The random rationing policy of the ISO turns out to be more successful in achieving lower bid prices and lower GenCo profits. In minimizing GenCos' total profit, a combination of pay-as-bid pricing rule and random rationing policy is observed to be the most promising. - Highlights: • An agent-based simulation of generation company behavior in electricity markets is developed. • Learning dynamics of companies is modeled with an extended Q-learning algorithm. • Different market clearing mechanisms of the regulator are compared. • Convergence to Nash equilibria is analyzed under different cases. • The level of competition in the market is studied.

The institutional stance in agent-based simulations

NARCIS (Netherlands)

Sileno, G.; Boer, A.; van Engers, T.; Filipe, J.; Fred, A.L.N.

2013-01-01

This paper presents a multi-agent framework intended to animate scenarios of compliance and non-compliance in a normative system. With the purpose of describing social human behaviour, we choose to reduce social complexity by creating models of the involved agents starting from stories, and

Dissemination of Cultural Norms and Values: Agent-Based Modeling

Directory of Open Access Journals (Sweden)

Denis Andreevich Degterev

2016-12-01

Full Text Available This article shows how agent-based modeling allows us to explore the mechanisms of the dissemination of cultural norms and values both within one country and in the whole world. In recent years, this type of simulation is particularly prevalent in the analysis of international relations, becoming more popular than the system dynamics and discrete event simulation. The use of agent-based modeling in the analysis of international relations is connected with the agent-structure problem in international relations. Structure and agents act as interdependent and dynamically changing in the process of interaction between entities. Agent-structure interaction could be modeled by means of the theory of complex adaptive systems with the use of agent-based modeling techniques. One of the first examples of the use of agent-based modeling in political science is a model of racial segregation T. Shellinga. On the basis of this model, the author shows how the change in behavioral patterns at micro-level impacts on the macro-level. Patterns are changing due to the dynamics of cultural norms and values, formed by mass-media and other social institutes. The author shows the main areas of modern application of agent-based modeling in international studies including the analysis of ethnic conflicts, the formation of international coalitions. Particular attention is paid to Robert Axelrod approach based on the use of genetic algorithms to the spread of cultural norms and values. Agent-based modeling shows how to how to create such conditions that the norms that originally are not shared by a significant part of the population, eventually spread everywhere. Practical application of these algorithms is shown by the author of the article on the example of the situation in Ukraine in 2015-2016. The article also reveals the mechanisms of international spread of cultural norms and values. The main think-tanks using agent-based modeling in international studies are

An agent-based simulation model of patient choice of health care providers in accountable care organizations.

Science.gov (United States)

Alibrahim, Abdullah; Wu, Shinyi

2018-03-01

Accountable care organizations (ACO) in the United States show promise in controlling health care costs while preserving patients' choice of providers. Understanding the effects of patient choice is critical in novel payment and delivery models like ACO that depend on continuity of care and accountability. The financial, utilization, and behavioral implications associated with a patient's decision to forego local health care providers for more distant ones to access higher quality care remain unknown. To study this question, we used an agent-based simulation model of a health care market composed of providers able to form ACO serving patients and embedded it in a conditional logit decision model to examine patients capable of choosing their care providers. This simulation focuses on Medicare beneficiaries and their congestive heart failure (CHF) outcomes. We place the patient agents in an ACO delivery system model in which provider agents decide if they remain in an ACO and perform a quality improving CHF disease management intervention. Illustrative results show that allowing patients to choose their providers reduces the yearly payment per CHF patient by $320, reduces mortality rates by 0.12 percentage points and hospitalization rates by 0.44 percentage points, and marginally increases provider participation in ACO. This study demonstrates a model capable of quantifying the effects of patient choice in a theoretical ACO system and provides a potential tool for policymakers to understand implications of patient choice and assess potential policy controls.

Understanding coupled natural and human systems on fire prone landscapes: integrating wildfire simulation into an agent based planning system.

Science.gov (United States)

Barros, Ana; Ager, Alan; Preisler, Haiganoush; Day, Michelle; Spies, Tom; Bolte, John

2015-04-01

Agent-based models (ABM) allow users to examine the long-term effects of agent decisions in complex systems where multiple agents and processes interact. This framework has potential application to study the dynamics of coupled natural and human systems where multiple stimuli determine trajectories over both space and time. We used Envision, a landscape based ABM, to analyze long-term wildfire dynamics in a heterogeneous, multi-owner landscape in Oregon, USA. Landscape dynamics are affected by land management policies, actors decisions, and autonomous processes such as vegetation succession, wildfire, or at a broader scale, climate change. Key questions include: 1) How are landscape dynamics influenced by policies and institutions, and 2) How do land management policies and actor decisions interact to produce intended and unintended consequences with respect to wildfire on fire-prone landscapes. Applying Envision to address these questions required the development of a wildfire module that could accurately simulate wildfires on the heterogeneous landscapes within the study area in terms of replicating historical fire size distribution, spatial distribution and fire intensity. In this paper we describe the development and testing of a mechanistic fire simulation system within Envision and application of the model on a 3.2 million fire prone landscape in central Oregon USA. The core fire spread equations use the Minimum Travel Time algorithm developed by M Finney. The model operates on a daily time step and uses a fire prediction system based on the relationship between energy release component and historical fires. Specifically, daily wildfire probabilities and sizes are generated from statistical analyses of historical fires in relation to daily ERC values. The MTT was coupled with the vegetation dynamics module in Envision to allow communication between the respective subsystem and effectively model fire effects and vegetation dynamics after a wildfire. Canopy and

Validating agent oriented methodology (AOM) for netlogo modelling and simulation

Science.gov (United States)

WaiShiang, Cheah; Nissom, Shane; YeeWai, Sim; Sharbini, Hamizan

2017-10-01

AOM (Agent Oriented Modeling) is a comprehensive and unified agent methodology for agent oriented software development. AOM methodology was proposed to aid developers with the introduction of technique, terminology, notation and guideline during agent systems development. Although AOM methodology is claimed to be capable of developing a complex real world system, its potential is yet to be realized and recognized by the mainstream software community and the adoption of AOM is still at its infancy. Among the reason is that there are not much case studies or success story of AOM. This paper presents two case studies on the adoption of AOM for individual based modelling and simulation. It demonstrate how the AOM is useful for epidemiology study and ecological study. Hence, it further validate the AOM in a qualitative manner.

Simulation and evaluation of urban rail transit network based on multi-agent approach

Directory of Open Access Journals (Sweden)

Xiangming Yao

2013-03-01

Full Text Available Purpose: Urban rail transit is a complex and dynamic system, which is difficult to be described in a global mathematical model for its scale and interaction. In order to analyze the spatial and temporal characteristics of passenger flow distribution and evaluate the effectiveness of transportation strategies, a new and comprehensive method depicted such dynamic system should be given. This study therefore aims at using simulation approach to solve this problem for subway network. Design/methodology/approach: In this thesis a simulation model based on multi-agent approach has been proposed, which is a well suited method to design complex systems. The model includes the specificities of passengers’ travelling behaviors and takes into account of interactions between travelers and trains. Findings: Research limitations/implications: We developed an urban rail transit simulation tool for verification of the validity and accuracy of this model, using real passenger flow data of Beijing subway network to take a case study, results show that our simulation tool can be used to analyze the characteristic of passenger flow distribution and evaluate operation strategies well. Practical implications: The main implications of this work are to provide decision support for traffic management, making train operation plan and dispatching measures in emergency. Originality/value: A new and comprehensive method to analyze and evaluate subway network is presented, accuracy and computational efficiency of the model has been confirmed and meet with the actual needs for large-scale network.

An agent-based information management model of the Chinese pig sector

NARCIS (Netherlands)

Osinga, S.A.; Kramer, M.R.; Hofstede, G.J.; Roozmand, O.; Beulens, A.J.M.

2010-01-01

This paper investigates the effect of a selected top-down measure (what-if scenario) on actual agent behaviour and total system behaviour by means of an agent-based simulation model, when agents’ behaviour cannot fully be managed because the agents are autonomous. The Chinese pork sector serves as

Improving Agent Based Modeling of Critical Incidents

Directory of Open Access Journals (Sweden)

Robert Till

2010-04-01

Full Text Available Agent Based Modeling (ABM is a powerful method that has been used to simulate potential critical incidents in the infrastructure and built environments. This paper will discuss the modeling of some critical incidents currently simulated using ABM and how they may be expanded and improved by using better physiological modeling, psychological modeling, modeling the actions of interveners, introducing Geographic Information Systems (GIS and open source models.

Assessing Consequential Scenarios in a Complex Operational Environment Using Agent Based Simulation

Science.gov (United States)

2017-03-16

capabilities and maturities of 4 subelements: cognition, judgment, emotion , and critical thinking. Each model represents these subelements differently...CADSIM) 102 5.2 Evaluating Agent-Based Technologies: Maturity Level and the Human Domain 103 5.2.1 Evaluation of Maturity Level 103 5.2.2 Human...describes the maturity of agent-based models, ranging from realistic caricatures to quantitatively characterized phenomena at the microlevel. This

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

Science.gov (United States)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

a Simulation-As Framework Facilitating Webgis Based Installation Planning

Science.gov (United States)

Zheng, Z.; Chang, Z. Y.; Fei, Y. F.

2017-09-01

Installation Planning is constrained by both natural and social conditions, especially for spatially sparse but functionally connected facilities. Simulation is important for proper deploy in space and configuration in function of facilities to make them a cohesive and supportive system to meet users' operation needs. Based on requirement analysis, we propose a framework to combine GIS and Agent simulation to overcome the shortness in temporal analysis and task simulation of traditional GIS. In this framework, Agent based simulation runs as a service on the server, exposes basic simulation functions, such as scenario configuration, simulation control, and simulation data retrieval to installation planners. At the same time, the simulation service is able to utilize various kinds of geoprocessing services in Agents' process logic to make sophisticated spatial inferences and analysis. This simulation-as-a-service framework has many potential benefits, such as easy-to-use, on-demand, shared understanding, and boosted performances. At the end, we present a preliminary implement of this concept using ArcGIS javascript api 4.0 and ArcGIS for server, showing how trip planning and driving can be carried out by agents.

An Agent-Based Simulation Model for Organizational Analysis

National Research Council Canada - National Science Library

Ruan, Sui; Gokhale, Swapna S; Pattipati, Krishna R

2006-01-01

In many fields, including engineering, management, and organizational science, simulation-based computational organization theory has been used to gain insight into the degree of match ("congruence...

Structuring Qualitative Data for Agent-Based Modelling

NARCIS (Netherlands)

Ghorbani, Amineh; Dijkema, Gerard P.J.; Schrauwen, Noortje

2015-01-01

Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a

An agent-based architecture for multimodal interaction

NARCIS (Netherlands)

Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

In this paper, an executable generic process model is proposed for combined verbal and non-verbal communication processes and their interaction. The agent-based architecture can be used to create multimodal interaction. The generic process model has been designed, implemented and used to simulate

An agent-based architecture for multimodal interaction

NARCIS (Netherlands)

Jonker, C.M.; Treur, J.; Wijngaards, W.C.A.

2001-01-01

In this paper, an executable generic process model is proposed for combined verbal and non-verbal communication processes and their interaction. The agent-based architecture can be used to create multimodal interaction. The generic process model has been designed, implemented and used to simulate

Stability of subsystem solutions in agent-based models

Science.gov (United States)

Perc, Matjaž

2018-01-01

The fact that relatively simple entities, such as particles or neurons, or even ants or bees or humans, give rise to fascinatingly complex behaviour when interacting in large numbers is the hallmark of complex systems science. Agent-based models are frequently employed for modelling and obtaining a predictive understanding of complex systems. Since the sheer number of equations that describe the behaviour of an entire agent-based model often makes it impossible to solve such models exactly, Monte Carlo simulation methods must be used for the analysis. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among agents that describe systems in biology, sociology or the humanities often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. This begets the question: when can we be certain that an observed simulation outcome of an agent-based model is actually stable and valid in the large system-size limit? The latter is key for the correct determination of phase transitions between different stable solutions, and for the understanding of the underlying microscopic processes that led to these phase transitions. We show that a satisfactory answer can only be obtained by means of a complete stability analysis of subsystem solutions. A subsystem solution can be formed by any subset of all possible agent states. The winner between two subsystem solutions can be determined by the average moving direction of the invasion front that separates them, yet it is crucial that the competing subsystem solutions are characterised by a proper composition and spatiotemporal structure before the competition starts. We use the spatial public goods game with diverse tolerance as an example, but the approach has relevance for a wide variety of agent-based models.

Modeling and simulating human teamwork behaviors using intelligent agents

Science.gov (United States)

Fan, Xiaocong; Yen, John

2004-12-01

Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

Multi-agent based distributed control architecture for microgrid energy management and optimization

International Nuclear Information System (INIS)

Basir Khan, M. Reyasudin; Jidin, Razali; Pasupuleti, Jagadeesh

2016-01-01

Highlights: • A new multi-agent based distributed control architecture for energy management. • Multi-agent coordination based on non-cooperative game theory. • A microgrid model comprised of renewable energy generation systems. • Performance comparison of distributed with conventional centralized control. - Abstract: Most energy management systems are based on a centralized controller that is difficult to satisfy criteria such as fault tolerance and adaptability. Therefore, a new multi-agent based distributed energy management system architecture is proposed in this paper. The distributed generation system is composed of several distributed energy resources and a group of loads. A multi-agent system based decentralized control architecture was developed in order to provide control for the complex energy management of the distributed generation system. Then, non-cooperative game theory was used for the multi-agent coordination in the system. The distributed generation system was assessed by simulation under renewable resource fluctuations, seasonal load demand and grid disturbances. The simulation results show that the implementation of the new energy management system proved to provide more robust and high performance controls than conventional centralized energy management systems.

An Agent-Based Dynamic Model of Politics, Fertility and Economic Development

Directory of Open Access Journals (Sweden)

Zining Yang

2016-08-01

Full Text Available In the political economy of development, government policy choices at a single point in time can dramatically affect a country's development path by impacting fertility, economic and political decisions across generations. Combining system dynamics and agent-based modeling approaches in a complex adaptive system, a simulation framework of the Politics of Fertility and Economic Development (POFED is formalized to understand the relationship between politics, economic, and demography change at both macro and micro levels. First, a new political capacity measurement is used; and the system dynamics model is validated with the latest data. Second, the endogenous attributes are fused with non-cooperative game theory in an agent-based framework to simulate the interactive political economic dynamics of individual intra-societal transactions. Finally, macro and micro levels are connected with policy levers of political capacity and political instability by merging system dynamics and agent-based components. This paper also explores the agent-based model's behavioral dynamics via simulation methods to identify paths towards economic development and political stability. This model demonstrates micro level human agency can act, react and interact, thus driving macro level dynamics, while macro structures provide political, social and economic environments that constrain or incentivize micro level human behavior.

Laser-based instrumentation for the detection of chemical agents

International Nuclear Information System (INIS)

Hartford, A. Jr.; Sander, R.K.; Quigley, G.P.; Radziemski, L.J.; Cremers, D.A.

1982-01-01

Several laser-based techniques are being evaluated for the remote, point, and surface detection of chemical agents. Among the methods under investigation are optoacoustic spectroscopy, laser-induced breakdown spectroscopy (LIBS), and synchronous detection of laser-induced fluorescence (SDLIF). Optoacoustic detection has already been shown to be capable of extremely sensitive point detection. Its application to remote sensing of chemical agents is currently being evaluated. Atomic emission from the region of a laser-generated plasma has been used to identify the characteristic elements contained in nerve (P and F) and blister (S and Cl) agents. Employing this LIBS approach, detection of chemical agent simulants dispersed in air and adsorbed on a variety of surfaces has been achieved. Synchronous detection of laser-induced fluorescence provides an attractive alternative to conventional LIF, in that an artificial narrowing of the fluorescence emission is obtained. The application of this technique to chemical agent simulants has been successfully demonstrated. 19 figures

Empirical agent-based modelling challenges and solutions

CERN Document Server

Barreteau, Olivier

2014-01-01

This instructional book showcases techniques to parameterise human agents in empirical agent-based models (ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through a variety of empirical applications.  It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM.  In order to facilitate learning, this text shares the valuable experiences of other modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level students and researchers studying simulation modeling in economics, sociology, ecology, and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides the empirical modeller with a set of 'recipes'  ready to be implemented. Agent-based modeling (AB...

Agent based Particle Swarm Optimization for Load Frequency Control of Distribution Grid

DEFF Research Database (Denmark)

Cha, Seung-Tae; Saleem, Arshad; Wu, Qiuwei

2012-01-01

This paper presents a Particle Swarm Optimization (PSO) based on multi-agent controller. Real-time digital simulator (RTDS) is used for modelling the power system, while a PSO based multi-agent LFC algorithm is developed in JAVA for communicating with resource agents and determines the scenario...... to stabilize the frequency and voltage after the system enters into the islanding operation mode. The proposed algorithm is based on the formulation of an optimization problem using agent based PSO. The modified IEEE 9-bus system is employed to illustrate the performance of the proposed controller via RTDS...

An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

Science.gov (United States)

Gidden, Matthew J.

Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy.

Directory of Open Access Journals (Sweden)

Theodore Eugene Day

Full Text Available Agent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort.The objective of this study was to develop an agent-based template to be used as a model for a patient with diabetic retinopathy (DR. This template may be replicated arbitrarily many times in order to generate a large cohort which is representative of a real-world population, upon which in-silico experimentation may be conducted.Agent-based template development was performed in java-based computer simulation suite AnyLogic Professional 6.6. The model was informed by medical data abstracted from 535 patient records representing a retrospective cohort of current patients of the VA St. Louis Healthcare System Eye clinic. Logistic regression was performed to determine the predictors associated with advancing stages of DR. Predicted probabilities obtained from logistic regression were used to generate the stage of DR in the simulated cohort.The simulated cohort of DR patients exhibited no significant deviation from the test population of real-world patients in proportion of stage of DR, duration of diabetes mellitus (DM, or the other abstracted predictors. Simulated patients after 10 years were significantly more likely to exhibit proliferative DR (P<0.001.Agent-based modeling is an emerging platform, capable of simulating large cohorts of individuals based on manageable data abstraction efforts. The modeling method described may be useful in simulating many different conditions where course of disease is described in categorical stages.

Simulated Environments with Animated Agents: Effects on Visual Attention, Emotion, Performance, and Perception

Science.gov (United States)

Romero-Hall, E.; Watson, G. S.; Adcock, A.; Bliss, J.; Adams Tufts, K.

2016-01-01

This research assessed how emotive animated agents in a simulation-based training affect the performance outcomes and perceptions of the individuals interacting in real time with the training application. A total of 56 participants consented to complete the study. The material for this investigation included a nursing simulation in which…

Integrated control of lateral and vertical vehicle dynamics based on multi-agent system

Science.gov (United States)

Huang, Chen; Chen, Long; Yun, Chaochun; Jiang, Haobin; Chen, Yuexia

2014-03-01

The existing research of the integrated chassis control mainly focuses on the different evaluation indexes and control strategy. Among the different evaluation indexes, the comprehensive properties are usually not considered based on the non-linear superposition principle. But, the control strategy has some shortages on tyre model with side-slip angle, road adhesion coefficient, vertical load and velocity. In this paper, based on belief, desire and intention(BDI)-agent model framework, the TYRE agent, electric power steering(EPS) agent and active suspension system(ASS) agent are proposed. In the system(SYS) agent, the coordination mechanism is employed to manage interdependences and conflicts among other agents, so as to improve the flexibility, adaptability, and robustness of the global control system. Due to the existence of the simulation demand of dynamic performance, the vehicle multi-body dynamics model is established by SIMPACK. And then the co-simulation analysis is conducted to evaluate the proposed multi-agent system(MAS) controller. The simulation results demonstrate that the MAS has good effect on the performance of EPS and ASS. Meantime, the better road feeling for the driver is provided considering the multiple and complex driving traffic. Finally, the MAS rapid control prototyping is built to conduct the real vehicle test. The test results are consistent to the simulation results, which verifies the correctness of simulation. The proposed research ensures the driving safety, enhances the handling stability, and improves the ride comfort.

Real-Time Agent-Based Modeling Simulation with in-situ Visualization of Complex Biological Systems: A Case Study on Vocal Fold Inflammation and Healing.

Science.gov (United States)

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

2016-05-01

We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.

Optimization of Intelligent Munition Warfare Using Agent-Based Simulation Software and Design of Experiments Methodology

National Research Council Canada - National Science Library

Floersheim, Bruce; Hou, Gene

2006-01-01

... mechanism for a number of vehicles caught in the killzone. Thus, it is useful to study and attempt to model through equations and simulation the interaction between enemy agents and these new munitions...

Integration agent-based models and GIS as a virtual urban dynamic laboratory

Science.gov (United States)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

Designing environmental campaigns by using agent-based simulations: strategies for changing environmental attitudes.

Science.gov (United States)

Mosler, Hans-Joachim; Martens, Thomas

2008-09-01

Agent-based computer simulation was used to create artificial communities in which each individual was constructed according to the principles of the elaboration likelihood model of Petty and Cacioppo [1986. The elaboration likelihood model of persuasion. In: Berkowitz, L. (Ed.), Advances in Experimental Social Psychology. Academic Press, New York, NY, pp. 123-205]. Campaigning strategies and community characteristics were varied systematically to understand and test their impact on attitudes towards environmental protection. The results show that strong arguments influence a green (environmentally concerned) population with many contacts most effectively, while peripheral cues have the greatest impact on a non-green population with fewer contacts. Overall, deeper information scrutiny increases the impact of strong arguments but is especially important for convincing green populations. Campaigns involving person-to-person communication are superior to mass-media campaigns because they can be adapted to recipients' characteristics.

The Effect of Food-Simulating Agents on the Bond Strength of Hard Chairside Reline Materials to Denture Base Resin.

Science.gov (United States)

Fatemi, Farzaneh Sadat; Vojdani, Mahroo; Khaledi, Amir Ali Reza

2018-06-08

To investigate the influence of food-simulating agents on the shear bond strength between direct hard liners and denture base acrylic resin. In addition, mode of failure was evaluated. One hundred fifty cylindrical columns of denture base resin were fabricated and bonded to three types of hard reline materials (Hard GC Reline, Tokuyama Rebase II Fast, TDV Cold Liner Rebase). Specimens of each reline material were divided into five groups (n = 10) to undergo 12-day immersion in distilled water, 0.02 N citric acid aqueous solution, heptane, and 40% ethanol/water solution at 37°C. The control group was not immersed in any solution. The shear bond strength test was performed, and the failure mode was determined. Statistics were analyzed with two-way ANOVA and chi-square test (α = 0.05). Significant interaction was found between the hard liners and food simulating agents (p < 0.001). The shear bond strength of Tokuyama in 40% ethanol and TDV in heptane decreased significantly (p = 0.001, p < 0.001 respectively); however, none of the solutions could significantly affect the shear bond strength of Hard GC Reline (p = 0.208). The mixed failure mode occurred more frequently in Hard GC Reline compared with the other liners (p < 0.001) and was predominant in specimens with higher bond strength values (p = 0.012). Food simulating agents did not adversely affect the shear bond strength of Hard GC Reline; however, ethanol and heptane decreased the bond strength of Tokuyama and TDV, respectively. These findings may provide support to dentists to recommend restricted consumption of some foods and beverages for patients who have to use dentures relined with certain hard liners. © 2018 by the American College of Prosthodontists.

Connectionist agent-based learning in bank-run decision making

Science.gov (United States)

Huang, Weihong; Huang, Qiao

2018-05-01

It is of utter importance for the policy makers, bankers, and investors to thoroughly understand the probability of bank-run (PBR) which was often neglected in the classical models. Bank-run is not merely due to miscoordination (Diamond and Dybvig, 1983) or deterioration of bank assets (Allen and Gale, 1998) but various factors. This paper presents the simulation results of the nonlinear dynamic probabilities of bank runs based on the global games approach, with the distinct assumption that heterogenous agents hold highly correlated but unidentical beliefs about the true payoffs. The specific technique used in the simulation is to let agents have an integrated cognitive-affective network. It is observed that, even when the economy is good, agents are significantly affected by the cognitive-affective network to react to bad news which might lead to bank-run. Both the rise of the late payoffs, R, and the early payoffs, r, will decrease the effect of the affective process. The increased risk sharing might or might not increase PBR, and the increase in late payoff is beneficial for preventing the bank run. This paper is one of the pioneers that links agent-based computational economics and behavioral economics.

Agent Based Modeling and Simulation of Pedestrian Crowds In Panic Situations

KAUST Repository

Alrashed, Mohammed

2016-11-01

The increasing occurrence of panic stampedes during mass events has motivated studying the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. The lack of understanding of panic stampedes still causes hundreds of fatalities each year, not to mention the scarce methodical studies of panic behavior capable of envisaging such crowd dynamics. Under those circumstances, there are thousands of fatalities and twice that many of injuries every year caused be crowd stampede worldwide, despite the tremendous efforts of crowd control and massive numbers of safekeeping forces. Pedestrian crowd dynamics are generally predictable in high-density crowds where pedestrians cannot move freely and thus gives rise to self-propelling interactions between pedestrians. Although every pedestrian has personal preferences, the motion dynamics can be modeled as a social force in such crowds. These forces are representations of internal preferences and objectives to perform certain actions or movements. The corresponding forces can be controlled for each individual to represent a different variety of behaviors that can be associated with panic situations such as escaping danger, clustering, and pushing. In this thesis, we use an agent-based model of pedestrian behavior in panic situations to predict the collective human behavior in such crowd dynamics. The proposed simulations suggests a practical way to alleviate fatalities and minimize the evacuation time in panic situations. Moreover, we introduce contagious panic and pushing behavior, resulting in a more realistic crowd dynamics model. The proposed methodology describes the intensity and spread of panic for each individual as a function of distances between pedestrians.

Developing an agent-based model on how different individuals solve complex problems

Directory of Open Access Journals (Sweden)

Ipek Bozkurt

2015-01-01

Full Text Available Purpose: Research that focuses on the emotional, mental, behavioral and cognitive capabilities of individuals has been abundant within disciplines such as psychology, sociology, and anthropology, among others. However, when facing complex problems, a new perspective to understand individuals is necessary. The main purpose of this paper is to develop an agent-based model and simulation to gain understanding on the decision-making and problem-solving abilities of individuals. Design/Methodology/approach: The micro-level analysis modeling and simulation paradigm Agent-Based Modeling Through the use of Agent-Based Modeling, insight is gained on how different individuals with different profiles deal with complex problems. Using previous literature from different bodies of knowledge, established theories and certain assumptions as input parameters, a model is built and executed through a computer simulation. Findings: The results indicate that individuals with certain profiles have better capabilities to deal with complex problems. Moderate profiles could solve the entire complex problem, whereas profiles within extreme conditions could not. This indicates that having a strong predisposition is not the ideal way when approaching complex problems, and there should always be a component from the other perspective. The probability that an individual may use these capabilities provided by the opposite predisposition provides to be a useful option. Originality/value: The originality of the present research stems from how individuals are profiled, and the model and simulation that is built to understand how they solve complex problems. The development of the agent-based model adds value to the existing body of knowledge within both social sciences, and modeling and simulation.

An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

Science.gov (United States)

Hu, Xiaolin; Puddy, Richard W.

This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

CATS-based Air Traffic Controller Agents

Science.gov (United States)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human

Using cheminformatics to find simulants for chemical warfare agents

Energy Technology Data Exchange (ETDEWEB)

Lavoie, J.; Srinivasan, Sree [Molecular Sciences and Engineering Team, U.S. Army Natick Soldier Research, Development and Engineering Center, 15 Kansas Street, Natick, MA 01760 (United States); Nagarajan, R., E-mail: Ramanathan.Nagarajan@us.army.mil [Molecular Sciences and Engineering Team, U.S. Army Natick Soldier Research, Development and Engineering Center, 15 Kansas Street, Natick, MA 01760 (United States)

2011-10-30

Highlights: {yields} Summary of chemical warfare agent (CWA) simulants in current use. {yields} Application of method of molecular similarity to CWA and simulants. {yields} Quantitative metric for CWA-simulant similarity. {yields} Rank ordering of simulants in current use. {yields} Potential of method to identify simulants for emerging agents. - Abstract: Direct experimentation with chemical warfare agents (CWA) to study important problems such as their permeation across protective barrier materials, decontamination of equipment and facilities, or the environmental transport and fate of CWAs is not feasible because of the obvious toxicity of the CWAs and associated restrictions on their laboratory use. The common practice is to use 'simulants,' namely, analogous chemicals that closely resemble the CWAs but are less toxic, with the expectation that the results attained for simulants can be correlated to how the CWAs would perform. Simulants have been traditionally chosen by experts, by means of intuition, using similarity in one or more physical properties (such as vapor pressure or aqueous solubility) or in the molecular structural features (such as functional groups) between the stimulant and the CWA. This work is designed to automate the simulant identification process backed by quantitative metrics, by means of chemical similarity search software routinely used in pharmaceutical drug discovery. The question addressed here is: By the metrics of such software, how similar are traditional simulants to CWAs? That is, what is the numerical 'distance' between each CWA and its customary simulants in the quantitative space of molecular descriptors? The answers show promise for finding close but less toxic simulants for the ever-increasing numbers of CWAs objectively and fast.

Using cheminformatics to find simulants for chemical warfare agents

International Nuclear Information System (INIS)

Lavoie, J.; Srinivasan, Sree; Nagarajan, R.

2011-01-01

Highlights: → Summary of chemical warfare agent (CWA) simulants in current use. → Application of method of molecular similarity to CWA and simulants. → Quantitative metric for CWA-simulant similarity. → Rank ordering of simulants in current use. → Potential of method to identify simulants for emerging agents. - Abstract: Direct experimentation with chemical warfare agents (CWA) to study important problems such as their permeation across protective barrier materials, decontamination of equipment and facilities, or the environmental transport and fate of CWAs is not feasible because of the obvious toxicity of the CWAs and associated restrictions on their laboratory use. The common practice is to use 'simulants,' namely, analogous chemicals that closely resemble the CWAs but are less toxic, with the expectation that the results attained for simulants can be correlated to how the CWAs would perform. Simulants have been traditionally chosen by experts, by means of intuition, using similarity in one or more physical properties (such as vapor pressure or aqueous solubility) or in the molecular structural features (such as functional groups) between the stimulant and the CWA. This work is designed to automate the simulant identification process backed by quantitative metrics, by means of chemical similarity search software routinely used in pharmaceutical drug discovery. The question addressed here is: By the metrics of such software, how similar are traditional simulants to CWAs? That is, what is the numerical 'distance' between each CWA and its customary simulants in the quantitative space of molecular descriptors? The answers show promise for finding close but less toxic simulants for the ever-increasing numbers of CWAs objectively and fast.

Can human-like Bots control collective mood: agent-based simulations of online chats

Science.gov (United States)

Tadić, Bosiljka; Šuvakov, Milovan

2013-10-01

Using an agent-based modeling approach, in this paper, we study self-organized dynamics of interacting agents in the presence of chat Bots. Different Bots with tunable ‘human-like’ attributes, which exchange emotional messages with agents, are considered, and the collective emotional behavior of agents is quantitatively analyzed. In particular, using detrended fractal analysis we determine persistent fluctuations and temporal correlations in time series of agent activity and statistics of avalanches carrying emotional messages of agents when Bots favoring positive/negative affects are active. We determine the impact of Bots and identify parameters that can modulate that impact. Our analysis suggests that, by these measures, the emotional Bots induce collective emotion among interacting agents by suitably altering the fractal characteristics of the underlying stochastic process. Positive emotion Bots are slightly more effective than negative emotion Bots. Moreover, Bots which periodically alternate between positive and negative emotion can enhance fluctuations in the system, leading to avalanches of agent messages that are reminiscent of self-organized critical states.

Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent-Based Modeling and Simulation

Directory of Open Access Journals (Sweden)

Sonja Kolen

2018-01-01

Full Text Available In future electrical distribution systems, component heterogeneity and their cyber-physical interactions through electrical lines and communication lead to emergent system behavior. As the distribution systems represent the largest part of an energy system with respect to the number of nodes and components, large-scale studies of their emergent behavior are vital for the development of decentralized control strategies. This paper presents and evaluates DistAIX, a novel agent-based modeling and simulation tool to conduct such studies. The major novelty is a parallelization of the entire model—including the power system, communication system, control, and all interactions—using processes instead of threads. Thereby, a distribution of the simulation to multiple computing nodes with a distributed memory architecture becomes possible. This makes DistAIX scalable and allows the inclusion of as many processing units in the simulation as desired. The scalability of DistAIX is demonstrated by simulations of large-scale scenarios. Additionally, the capability of observing emergent behavior is demonstrated for an exemplary distribution grid with a large number of interacting components.

Study of photo-oxidative reactivity of sunscreening agents based on photo-oxidation of uric acid by kinetic Monte Carlo simulation.

Science.gov (United States)

Moradmand Jalali, Hamed; Bashiri, Hadis; Rasa, Hossein

2015-05-01

In the present study, the mechanism of free radical production by light-reflective agents in sunscreens (TiO2, ZnO and ZrO2) was obtained by applying kinetic Monte Carlo simulation. The values of the rate constants for each step of the suggested mechanism have been obtained by simulation. The effect of the initial concentration of mineral oxides and uric acid on the rate of uric acid photo-oxidation by irradiation of some sun care agents has been studied. The kinetic Monte Carlo simulation results agree qualitatively with the existing experimental data for the production of free radicals by sun care agents. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NARCIS (Netherlands)

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

2011-01-01

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

Multi-agent simulations for emergency situations in an airport scenario

Directory of Open Access Journals (Sweden)

Ana Cristina BICHARRA

2012-12-01

Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} This paper presents a multi-agent framework using Net- Logo to simulate human and collective behaviors during emergency evacuations. Emergency situation appears when an unexpected event occurs. In indoor emergency situation, evacuation plans defined by facility manager explain procedure and safety ways to follow in an emergency situation. A critical and public scenario is an airportwhere there is an everyday transit of thousands of people. In this scenario the importance is related with incidents statistics regarding overcrowding and crushing in public buildings. Simulation has the objective of evaluating building layouts considering several possible configurations. Agents could be based on reactive behavior like avoid danger or follow other agent, or in deliberative behavior based on BDI model. This tool provides decision support in a real emergency scenario like an airport, analyzing alternative solutions to the evacuation process.

Multi-agent simulations for emergency situations in an airport scenario

Directory of Open Access Journals (Sweden)

José Manuel MOLINA

2013-06-01

Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} This paper presents a multi-agent framework using Net- Logo to simulate human and collective behaviors during emergency evacuations. Emergency situation appears when an unexpected event occurs. In indoor emergency situation, evacuation plans defined by facility manager explain procedure and safety ways to follow in an emergency situation. A critical and public scenario is an airport where there is an everyday transit of thousands of people. In this scenario the importance is related with incidents statistics regarding overcrowding and crushing in public buildings. Simulation has the objective of evaluating building layouts considering several possible configurations. Agents could be based on reactive behavior like avoid danger or follow other agent, or in deliberative behavior based on BDI model. This tool provides decision support in a real emergency scenario like an airport, analyzing alternative solutions to the evacuation process.

TACOP : A cognitive agent for a naval training simulation environment

NARCIS (Netherlands)

Doesburg, W.A. van; Heuvelink, A.; Broek, E.L. van den

2005-01-01

This paper describes how cognitive modeling can be exploited in the design of software agents that support naval training sessions. The architecture, specifications, and embedding of the cognitive agent in a simulation environment are described. Subsequently, the agent's functioning was evaluated in

Agent-based Modeling Methodology for Analyzing Weapons Systems

Science.gov (United States)

2015-03-26

technique involve model structure, system representation and the degree of validity, coupled with the simplicity, of the overall model. ABM is best suited... system representation of the air combat system . We feel that a simulation model that combines ABM with equation-based representation of weapons and...AGENT-BASED MODELING METHODOLOGY FOR ANALYZING WEAPONS SYSTEMS THESIS Casey D. Connors, Major, USA

Modeling collective emotions: a stochastic approach based on Brownian agents

International Nuclear Information System (INIS)

Schweitzer, F.

2010-01-01

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a super linear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities. (author)

Can human-like Bots control collective mood: agent-based simulations of online chats

International Nuclear Information System (INIS)

Tadić, Bosiljka; Šuvakov, Milovan

2013-01-01

Using an agent-based modeling approach, in this paper, we study self-organized dynamics of interacting agents in the presence of chat Bots. Different Bots with tunable ‘human-like’ attributes, which exchange emotional messages with agents, are considered, and the collective emotional behavior of agents is quantitatively analyzed. In particular, using detrended fractal analysis we determine persistent fluctuations and temporal correlations in time series of agent activity and statistics of avalanches carrying emotional messages of agents when Bots favoring positive/negative affects are active. We determine the impact of Bots and identify parameters that can modulate that impact. Our analysis suggests that, by these measures, the emotional Bots induce collective emotion among interacting agents by suitably altering the fractal characteristics of the underlying stochastic process. Positive emotion Bots are slightly more effective than negative emotion Bots. Moreover, Bots which periodically alternate between positive and negative emotion can enhance fluctuations in the system, leading to avalanches of agent messages that are reminiscent of self-organized critical states. (paper)

Agent-Based Model Approach to Complex Phenomena in Real Economy

Science.gov (United States)

Iyetomi, H.; Aoyama, H.; Fujiwara, Y.; Ikeda, Y.; Souma, W.

An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents are described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm directed by the ``profit maximization" principle is suppressed by a concept of ``going concern". Possibility of bankruptcy of firms is also introduced by incorporating a retardation effect of information on firms' decision. The firms, mutually interacting through the monopolistic bank, become heterogeneous in the course of temporal evolution. Statistical properties of firms' dynamics obtained by simulations based on the model are discussed in light of observations in the real economy.

Multi Agent System Based Wide Area Protection against Cascading Events

DEFF Research Database (Denmark)

Liu, Zhou; Chen, Zhe; Liu, Leo

2012-01-01

In this paper, a multi-agent system based wide area protection scheme is proposed in order to prevent long term voltage instability induced cascading events. The distributed relays and controllers work as a device agent which not only executes the normal function automatically but also can...... the effectiveness of proposed protection strategy. The simulation results indicate that the proposed multi agent control system can effectively coordinate the distributed relays and controllers to prevent the long term voltage instability induced cascading events....

Agent-based Modeling Automated: Data-driven Generation of Innovation Diffusion Models

NARCIS (Netherlands)

Jensen, T.; Chappin, E.J.L.

2016-01-01

Simulation modeling is useful to gain insights into driving mechanisms of diffusion of innovations. This study aims to introduce automation to make identification of such mechanisms with agent-based simulation modeling less costly in time and labor. We present a novel automation procedure in which

Can agent based models effectively reduce fisheries management implementation uncertainty?

Science.gov (United States)

Drexler, M.

2016-02-01

Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

Study of photo-oxidative reactivity of sunscreening agents based on photo-oxidation of uric acid by kinetic Monte Carlo simulation

International Nuclear Information System (INIS)

Moradmand Jalali, Hamed; Bashiri, Hadis; Rasa, Hossein

2015-01-01

In the present study, the mechanism of free radical production by light-reflective agents in sunscreens (TiO 2 , ZnO and ZrO 2 ) was obtained by applying kinetic Monte Carlo simulation. The values of the rate constants for each step of the suggested mechanism have been obtained by simulation. The effect of the initial concentration of mineral oxides and uric acid on the rate of uric acid photo-oxidation by irradiation of some sun care agents has been studied. The kinetic Monte Carlo simulation results agree qualitatively with the existing experimental data for the production of free radicals by sun care agents. - Highlights: • The mechanism and kinetics of uric acid photo-oxidation by irradiation of sun care agents has been obtained by simulation. • The mechanism has been used for free radical production of TiO 2 (rutile and anatase), ZnO and ZrO 2 . • The ratios of photo-activity of ZnO to anastase, rutile and ZrO have been obtained. • By doubling the initial concentrations of mineral oxide, the rate of reaction was doubled. • The optimum ratio of initial concentration of mineral oxides to uric acid has been obtained

Multi-agent cooperation rescue algorithm based on influence degree and state prediction

Science.gov (United States)

Zheng, Yanbin; Ma, Guangfu; Wang, Linlin; Xi, Pengxue

2018-04-01

Aiming at the multi-agent cooperative rescue in disaster, a multi-agent cooperative rescue algorithm based on impact degree and state prediction is proposed. Firstly, based on the influence of the information in the scene on the collaborative task, the influence degree function is used to filter the information. Secondly, using the selected information to predict the state of the system and Agent behavior. Finally, according to the result of the forecast, the cooperative behavior of Agent is guided and improved the efficiency of individual collaboration. The simulation results show that this algorithm can effectively solve the cooperative rescue problem of multi-agent and ensure the efficient completion of the task.

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

Science.gov (United States)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

Agent Based Modeling as an Educational Tool

Science.gov (United States)

Fuller, J. H.; Johnson, R.; Castillo, V.

2012-12-01

Motivation is a key element in high school education. One way to improve motivation and provide content, while helping address critical thinking and problem solving skills, is to have students build and study agent based models in the classroom. This activity visually connects concepts with their applied mathematical representation. "Engaging students in constructing models may provide a bridge between frequently disconnected conceptual and mathematical forms of knowledge." (Levy and Wilensky, 2011) We wanted to discover the feasibility of implementing a model based curriculum in the classroom given current and anticipated core and content standards.; Simulation using California GIS data ; Simulation of high school student lunch popularity using aerial photograph on top of terrain value map.

An Adaptive Agent-Based Model of Homing Pigeons: A Genetic Algorithm Approach

Directory of Open Access Journals (Sweden)

Francis Oloo

2017-01-01

Full Text Available Conventionally, agent-based modelling approaches start from a conceptual model capturing the theoretical understanding of the systems of interest. Simulation outcomes are then used “at the end” to validate the conceptual understanding. In today’s data rich era, there are suggestions that models should be data-driven. Data-driven workflows are common in mathematical models. However, their application to agent-based models is still in its infancy. Integration of real-time sensor data into modelling workflows opens up the possibility of comparing simulations against real data during the model run. Calibration and validation procedures thus become automated processes that are iteratively executed during the simulation. We hypothesize that incorporation of real-time sensor data into agent-based models improves the predictive ability of such models. In particular, that such integration results in increasingly well calibrated model parameters and rule sets. In this contribution, we explore this question by implementing a flocking model that evolves in real-time. Specifically, we use genetic algorithms approach to simulate representative parameters to describe flight routes of homing pigeons. The navigation parameters of pigeons are simulated and dynamically evaluated against emulated GPS sensor data streams and optimised based on the fitness of candidate parameters. As a result, the model was able to accurately simulate the relative-turn angles and step-distance of homing pigeons. Further, the optimised parameters could replicate loops, which are common patterns in flight tracks of homing pigeons. Finally, the use of genetic algorithms in this study allowed for a simultaneous data-driven optimization and sensitivity analysis.

Agent-Based Modeling in Systems Pharmacology.

Science.gov (United States)

Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

2015-11-01

Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

QoS Negotiation and Renegotiation Based on Mobile Agents

Institute of Scientific and Technical Information of China (English)

ZHANG Shi-bing; ZHANG Deng-yin

2006-01-01

The Quality of Service (QoS) has received more and more attention since QoS becomes increasingly important in the Internet development. Mobile software agents represent a valid alternative to the implementation of strategies for the negotiation. In this paper, a QoS negotiation and renegotiation system architecture based on mobile agents is proposed. The agents perform the task in the whole process. Therefore, such a system can reduce the network load, overcome latency, and avoid frequent exchange information between clients and server. The simulation results show that the proposed system could improve the network resource utility about 10%.

The Basic Immune Simulator: An agent-based model to study the interactions between innate and adaptive immunity

Directory of Open Access Journals (Sweden)

Orosz Charles G

2007-09-01

Full Text Available Abstract Background We introduce the Basic Immune Simulator (BIS, an agent-based model created to study the interactions between the cells of the innate and adaptive immune system. Innate immunity, the initial host response to a pathogen, generally precedes adaptive immunity, which generates immune memory for an antigen. The BIS simulates basic cell types, mediators and antibodies, and consists of three virtual spaces representing parenchymal tissue, secondary lymphoid tissue and the lymphatic/humoral circulation. The BIS includes a Graphical User Interface (GUI to facilitate its use as an educational and research tool. Results The BIS was used to qualitatively examine the innate and adaptive interactions of the immune response to a viral infection. Calibration was accomplished via a parameter sweep of initial agent population size, and comparison of simulation patterns to those reported in the basic science literature. The BIS demonstrated that the degree of the initial innate response was a crucial determinant for an appropriate adaptive response. Deficiency or excess in innate immunity resulted in excessive proliferation of adaptive immune cells. Deficiency in any of the immune system components increased the probability of failure to clear the simulated viral infection. Conclusion The behavior of the BIS matches both normal and pathological behavior patterns in a generic viral infection scenario. Thus, the BIS effectively translates mechanistic cellular and molecular knowledge regarding the innate and adaptive immune response and reproduces the immune system's complex behavioral patterns. The BIS can be used both as an educational tool to demonstrate the emergence of these patterns and as a research tool to systematically identify potential targets for more effective treatment strategies for diseases processes including hypersensitivity reactions (allergies, asthma, autoimmunity and cancer. We believe that the BIS can be a useful addition to

Flexible carbon nanotube sensors for nerve agent simulants

Energy Technology Data Exchange (ETDEWEB)

Cattanach, Kyle; Kulkarni, Rashmi D; Kozlov, Mikhail; Manohar, Sanjeev K [Alan G MacDiarmid Center for Innovation, Department of Chemistry, University of Texas at Dallas, Richardson 75083-0688 (United States)

2006-08-28

Chemiresistor-based vapour sensors made from network films of single-walled carbon nanotube (SWNT) bundles on flexible plastic substrates (polyethylene terephthalate, PET) can be used to detect chemical warfare agent simulants for the nerve agents Sarin (diisopropyl methylphosphonate, DIMP) and Soman (dimethyl methylphosphonate, DMMP). Large, reproducible resistance changes (75-150%), are observed upon exposure to DIMP or DMMP vapours, and concentrations as low as 25 ppm can be detected. Robust sensor response to simulant vapours is observed even in the presence of large equilibrium concentrations of interferent vapours commonly found in battle-space environments, such as hexane, xylene and water (10 000 ppm each), suggesting that both DIMP and DMMP vapours are capable of selectively displacing other vapours from the walls of the SWNTs. Response to these interferent vapours can be effectively filtered out by using a 2 {mu}m thick barrier film of the chemoselective polymer polyisobutylene (PIB) on the SWNT surface. These network films are composed of a 1-2 {mu}m thick non-woven mesh of SWNT bundles (15-30 nm diameter), whose sensor response is qualitatively and quantitatively different from previous studies on individual SWNTs, or a network of individual SWNTs, suggesting that vapour sorption at interbundle sites could be playing an important role. This study also shows that the line patterning method used in device fabrication to obtain any desired pattern of films of SWNTs on flexible substrates can be used to rapidly screen simulants at high concentrations before developing more complicated sensor systems.

Integrating the simulation of domestic water demand behaviour to an urban water model using agent based modelling

Science.gov (United States)

Koutiva, Ifigeneia; Makropoulos, Christos

2015-04-01

The urban water system's sustainable evolution requires tools that can analyse and simulate the complete cycle including both physical and cultural environments. One of the main challenges, in this regard, is the design and development of tools that are able to simulate the society's water demand behaviour and the way policy measures affect it. The effects of these policy measures are a function of personal opinions that subsequently lead to the formation of people's attitudes. These attitudes will eventually form behaviours. This work presents the design of an ABM tool for addressing the social dimension of the urban water system. The created tool, called Urban Water Agents' Behaviour (UWAB) model, was implemented, using the NetLogo agent programming language. The main aim of the UWAB model is to capture the effects of policies and environmental pressures to water conservation behaviour of urban households. The model consists of agents representing urban households that are linked to each other creating a social network that influences the water conservation behaviour of its members. Household agents are influenced as well by policies and environmental pressures, such as drought. The UWAB model simulates behaviour resulting in the evolution of water conservation within an urban population. The final outcome of the model is the evolution of the distribution of different conservation levels (no, low, high) to the selected urban population. In addition, UWAB is implemented in combination with an existing urban water management simulation tool, the Urban Water Optioneering Tool (UWOT) in order to create a modelling platform aiming to facilitate an adaptive approach of water resources management. For the purposes of this proposed modelling platform, UWOT is used in a twofold manner: (1) to simulate domestic water demand evolution and (2) to simulate the response of the water system to the domestic water demand evolution. The main advantage of the UWAB - UWOT model

An integrated ant colony optimization approach to compare strategies of clearing market in electricity markets. Agent-based simulation

International Nuclear Information System (INIS)

Azadeh, A.; Maleki-Shoja, B.; Skandari, M.R.

2010-01-01

In this paper, an innovative model of agent based simulation, based on Ant Colony Optimization (ACO) algorithm is proposed in order to compare three available strategies of clearing wholesale electricity markets, i.e. uniform, pay-as-bid, and generalized Vickrey rules. The supply side actors of the power market are modeled as adaptive agents who learn how to bid strategically to optimize their profit through indirect interaction with other actors of the market. The proposed model is proper for bidding functions with high number of dimensions and enables modelers to avoid curse of dimensionality as dimension grows. Test systems are then used to study the behavior of each pricing rule under different degrees of competition and heterogeneity. Finally, the pricing rules are comprehensively compared using different economic criteria such as average cleared price, efficiency of allocation, and price volatility. Also, principle component analysis (PCA) is used to rank and select the best price rule. To the knowledge of the authors, this is the first study that uses ACO for assessing strategies of wholesale electricity market. (author)

Agent-based power sharing scheme for active hybrid power sources

Science.gov (United States)

Jiang, Zhenhua

The active hybridization technique provides an effective approach to combining the best properties of a heterogeneous set of power sources to achieve higher energy density, power density and fuel efficiency. Active hybrid power sources can be used to power hybrid electric vehicles with selected combinations of internal combustion engines, fuel cells, batteries, and/or supercapacitors. They can be deployed in all-electric ships to build a distributed electric power system. They can also be used in a bulk power system to construct an autonomous distributed energy system. An important aspect in designing an active hybrid power source is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. This paper presents an agent-based power sharing scheme for active hybrid power sources. To demonstrate the effectiveness of the proposed agent-based power sharing scheme, simulation studies are performed for a hybrid power source that can be used in a solar car as the main propulsion power module. Simulation results clearly indicate that the agent-based control framework is effective to coordinate the various energy sources and manage the power/voltage profiles.

Using Model Replication to Improve the Reliability of Agent-Based Models

Science.gov (United States)

Zhong, Wei; Kim, Yushim

The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas

Directory of Open Access Journals (Sweden)

Liang Emlyn Yang

2018-04-01

Full Text Available Several approaches have been used to assess potential human exposure to environmental stresses and achieve optimal results under various conditions, such as for example, for different scales, groups of people, or points in time. A thorough literature review in this paper identifies the research gap regarding modeling approaches for assessing human exposure to environment stressors, and it indicates that microsimulation tools are becoming increasingly important in human exposure assessments of urban environments, in which each person is simulated individually and continuously. The paper further describes an agent-based model (ABM framework that can dynamically simulate human exposure levels, along with their daily activities, in urban areas that are characterized by environmental stresses such as air pollution and heat stress. Within the framework, decision-making processes can be included for each individual based on rule-based behavior in order to achieve goals under changing environmental conditions. The ideas described in this paper are implemented in a free and open source NetLogo platform. A basic modeling scenario of the ABM framework in Hamburg, Germany, demonstrates its utility in various urban environments and individual activity patterns, as well as its portability to other models, programs, and frameworks. The prototype model can potentially be extended to support environmental incidence management through exploring the daily routines of different groups of citizens, and comparing the effectiveness of different strategies. Further research is needed to fully develop an operational version of the model.

Study of photo-oxidative reactivity of sunscreening agents based on photo-oxidation of uric acid by kinetic Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Moradmand Jalali, Hamed; Bashiri, Hadis, E-mail: hbashiri@kashanu.ac.ir; Rasa, Hossein

2015-05-01

In the present study, the mechanism of free radical production by light-reflective agents in sunscreens (TiO{sub 2}, ZnO and ZrO{sub 2}) was obtained by applying kinetic Monte Carlo simulation. The values of the rate constants for each step of the suggested mechanism have been obtained by simulation. The effect of the initial concentration of mineral oxides and uric acid on the rate of uric acid photo-oxidation by irradiation of some sun care agents has been studied. The kinetic Monte Carlo simulation results agree qualitatively with the existing experimental data for the production of free radicals by sun care agents. - Highlights: • The mechanism and kinetics of uric acid photo-oxidation by irradiation of sun care agents has been obtained by simulation. • The mechanism has been used for free radical production of TiO{sub 2} (rutile and anatase), ZnO and ZrO{sub 2}. • The ratios of photo-activity of ZnO to anastase, rutile and ZrO have been obtained. • By doubling the initial concentrations of mineral oxide, the rate of reaction was doubled. • The optimum ratio of initial concentration of mineral oxides to uric acid has been obtained.

Modeling the transport of chemical warfare agents and simulants in polymeric substrates for reactive decontamination

Science.gov (United States)

Pearl, Thomas; Mantooth, Brent; Varady, Mark; Willis, Matthew

2014-03-01

Chemical warfare agent simulants are often used for environmental testing in place of highly toxic agents. This work sets the foundation for modeling decontamination of absorbing polymeric materials with the focus on determining relationships between agents and simulants. The correlations of agents to simulants must consider the three way interactions in the chemical-material-decontaminant system where transport and reaction occur in polymer materials. To this end, diffusion modeling of the subsurface transport of simulants and live chemical warfare agents was conducted for various polymer systems (e.g., paint coatings) with and without reaction pathways with applied decontamination. The models utilized 1D and 2D finite difference diffusion and reaction models to simulate absorption and reaction in the polymers, and subsequent flux of the chemicals out of the polymers. Experimental data including vapor flux measurements and dynamic contact angle measurements were used to determine model input parameters. Through modeling, an understanding of the relationship of simulant to live chemical warfare agent was established, focusing on vapor emission of agents and simulants from materials.

Agent-based modelling in synthetic biology.

Science.gov (United States)

Gorochowski, Thomas E

2016-11-30

Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

Evaluating Water Demand Using Agent-Based Modeling

Science.gov (United States)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

An agent-based model for diffusion of electric vehicles

NARCIS (Netherlands)

Kangur, Ayla; Jager, Wander; Verbrugge, Rineke; Bockarjova, Marija

2017-01-01

The transition from fuel cars to electric cars is a large-scale process involving many interactions between consumers and other stakeholders over decades. To explore how policies may interact with consumer behavior over such a long time period, we developed an agent-based social simulation model. In

Artificial force fields for multi-agent simulations of maritime traffic and risk estimation

NARCIS (Netherlands)

Xiao, F.; Ligteringen, H.; Van Gulijk, C.; Ale, B.J.M.

2012-01-01

A probabilistic risk model is designed to estimate probabilities of collisions for shipping accidents in busy waterways. We propose a method based on multi-agent simulation that uses an artificial force field to model ship maneuvers. The artificial force field is calibrated by AIS data (Automatic

Toward Simulating Realistic Pursuit-Evasion Using a Roadmap-Based Approach

KAUST Repository

Rodriguez, Samuel; Denny, Jory; Zourntos, Takis; Amato, Nancy M.

2010-01-01

In this work, we describe an approach for modeling and simulating group behaviors for pursuit-evasion that uses a graph-based representation of the environment and integrates multi-agent simulation with roadmap-based path planning. We demonstrate

Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics

Science.gov (United States)

Saeedi, Sara

2018-06-01

With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving

Agent-Based Coordination Model for Designing Transportation Applications

OpenAIRE

BADEIG, F; BALBO, F; SCEMAMA, G; ZARGAYOUNA, M

2008-01-01

This paper presents an environment-centered approach to design multi-agent solutions to transportation problems. Based on the Property-based Coordination Principle (PbC), the objective of our approach is to solve three recurrent issues in the design of these solutions: the knowledge problem, the space-time dimension and the dynamics of the real environment. To demonstrate the benefits of our approach, two completely different applications, a demand-responsive transportation system and a simul...

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

Science.gov (United States)

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

Towards a complex systems approach in sports injury research: simulating running-related injury development with agent-based modelling.

Science.gov (United States)

Hulme, Adam; Thompson, Jason; Nielsen, Rasmus Oestergaard; Read, Gemma J M; Salmon, Paul M

2018-06-18

There have been recent calls for the application of the complex systems approach in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. Therefore, our objective was to use a computational modelling method and develop a dynamic simulation in sports injury research. Agent-based modelling (ABM) was used to model the occurrence of sports injury in a synthetic athlete population. The ABM was developed based on sports injury causal frameworks and was applied in the context of distance running-related injury (RRI). Using the acute:chronic workload ratio (ACWR), we simulated the dynamic relationship between changes in weekly running distance and RRI through the manipulation of various 'athlete management tools'. The findings confirmed that building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a 'hard ceiling' dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. The presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM and other simulation-based techniques could be considered as a complementary and alternative methodological approach in sports injury research. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Identification of walking human model using agent-based modelling

Science.gov (United States)

Shahabpoor, Erfan; Pavic, Aleksandar; Racic, Vitomir

2018-03-01

The interaction of walking people with large vibrating structures, such as footbridges and floors, in the vertical direction is an important yet challenging phenomenon to describe mathematically. Several different models have been proposed in the literature to simulate interaction of stationary people with vibrating structures. However, the research on moving (walking) human models, explicitly identified for vibration serviceability assessment of civil structures, is still sparse. In this study, the results of a comprehensive set of FRF-based modal tests were used, in which, over a hundred test subjects walked in different group sizes and walking patterns on a test structure. An agent-based model was used to simulate discrete traffic-structure interactions. The occupied structure modal parameters found in tests were used to identify the parameters of the walking individual's single-degree-of-freedom (SDOF) mass-spring-damper model using 'reverse engineering' methodology. The analysis of the results suggested that the normal distribution with the average of μ = 2.85Hz and standard deviation of σ = 0.34Hz can describe human SDOF model natural frequency. Similarly, the normal distribution with μ = 0.295 and σ = 0.047 can describe the human model damping ratio. Compared to the previous studies, the agent-based modelling methodology proposed in this paper offers significant flexibility in simulating multi-pedestrian walking traffics, external forces and simulating different mechanisms of human-structure and human-environment interaction at the same time.

Multi-agent based modeling for electric vehicle integration in a distribution network operation

DEFF Research Database (Denmark)

Hu, Junjie; Morais, Hugo; Lind, Morten

2016-01-01

The purpose of this paper is to present a multi-agent based modeling technology for simulating and operating a hierarchical energy management of a power distribution system with focus on EVs integration. The proposed multi-agent system consists of four types of agents: i) Distribution system...... operator (DSO) technical agent and ii) DSO market agents that both belong to the top layer of the hierarchy and their roles are to manage the distribution network by avoiding grid congestions and using congestion prices to coordinate the energy scheduled; iii) Electric vehicle virtual power plant agents...

A standard protocol for describing individual-based and agent-based models

Science.gov (United States)

Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

2006-01-01

Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

A Multi-Agent Approach to the Simulation of Robotized Manufacturing Systems

Science.gov (United States)

Foit, K.; Gwiazda, A.; Banaś, W.

2016-08-01

The recent years of eventful industry development, brought many competing products, addressed to the same market segment. The shortening of a development cycle became a necessity if the company would like to be competitive. Because of switching to the Intelligent Manufacturing model the industry search for new scheduling algorithms, while the traditional ones do not meet the current requirements. The agent-based approach has been considered by many researchers as an important way of evolution of modern manufacturing systems. Due to the properties of the multi-agent systems, this methodology is very helpful during creation of the model of production system, allowing depicting both processing and informational part. The complexity of such approach makes the analysis impossible without the computer assistance. Computer simulation still uses a mathematical model to recreate a real situation, but nowadays the 2D or 3D virtual environments or even virtual reality have been used for realistic illustration of the considered systems. This paper will focus on robotized manufacturing system and will present the one of possible approaches to the simulation of such systems. The selection of multi-agent approach is motivated by the flexibility of this solution that offers the modularity, robustness and autonomy.

Agent-Based Approach for Modelling the Labour Migration from China to Russia

Directory of Open Access Journals (Sweden)

Valeriy Leonidovich Makarov

2017-06-01

Full Text Available The article describes the process of labour migration from China to Russia and shows its modelling using the agent-based approach. This approach allows us to simulate an artificial society in a computer program taking into account the diversity of individuals under consideration, as well as to model a set of laws and rules of conduct that make up the institutional environment in which the members of this society live. A brief review and analysis of agent-based migration models presented in the foreign literature are given. The agent-based model of labour migration from China to Russia developed by the Central Economic Mathematical Institute of the Russian Academy of Sciences simulates human behaviour close to reality, which is based on their internal purposes, determining the agents choice of territory as a place of residence. Therefore, at the development of the agents of the model and their behaviour algorithms, as well as the organization of the environment in which they exist and interact, the main characteristics of the population of two neighbouring countries and their demographic processes have been considered. Using the model, two experiments have been conducted. The purpose of the first of them was to assess the effect of depreciation of the rubble against the yuan on the overall indexes of labour migration, as well as its structure. In the second experiment, the procedure of the search of the information by agents for the migratory decision-making was changing. Namely, all generalizing information on the average salary by types of activity and skill level of employees, both in China and Russia, became available to all agents irrespective of their qualification level.

Novel Role of Rural Official Organization in the Biomass-Based Power Supply Chain in China: A Combined Game Theory and Agent-Based Simulation Approach

Directory of Open Access Journals (Sweden)

Kaiyan Luo

2016-08-01

Full Text Available Developing biomass-based power generation is helpful for China to reduce the dependence on fossil fuels and to release the targets of carbon emission peak. The decentralized farming method leads to Chinese farmers’ weak willingness to collect and sell crop residues to biomass-based power plants. The purpose of this paper is to solve the issue by proposing a novel biomass feedstock supply model with China’s rural official organization—villagers’ committee, which has great influence on villagers’ decision making. Introducing it into the biomass-based power supply chain is beneficial to motivating farmers’ supplying enthusiasm. A combined game theory and agent-based simulation approach is applied to study the effectiveness of this new supply model. Multiple simulation scenarios are built to study impacts of different simulation parameters, and results show that farmers tend to supply more biomass material for electricity production in the proposed villagers’ committee model, compared with the two conventional supply models, direct-deal and broker models. The supply model incorporating the rural official organization can ensure the feedstock sufficiency for plants. A proper model design depends on the feed-in tariff subsidy for biomass-based electricity, feedstock shipping distance, performance appraisal system of the villagers’ committee, as well as farmers’ utility weights on net income and public service improvement.

Analysis of Interactions of Key Stakeholders on B2C e-Markets - Agent Based Modelling and Simulation Approach

Directory of Open Access Journals (Sweden)

Marković Aleksandar

2016-05-01

Full Text Available Background/purpose: This paper discusses the application of ABMS - agent-based modelling and simulation in the analysis of customer behaviour on B2C e-commerce websites as well as in the analysis of various business decisions upon the effects of on-line sales. The continuous development and dynamics in the field of e-commerce requires application of advanced decision-making tools. These tools must be able to process, in a short time period, a large amount of data generated by the e-commerce systems and enable the use of acquired data for making quality business decisions.

A Multi Agent Based Model for Airport Service Planning

Directory of Open Access Journals (Sweden)

W.H. Ip

2010-09-01

Full Text Available Aviation industry is highly dynamic and demanding in nature that time and safety are the two most important factors while one of the major sources of delay is aircraft on ground because of it complexity, a lot of machinery like vehicles are involved and lots of communication are involved. As one of the aircraft ground services providers in Hong Kong International Airport, China Aircraft Services Limited (CASL aims to increase competitiveness by better its service provided while minimizing cost is also needed. One of the ways is to optimize the number of maintenance vehicles allocated in order to minimize chance of delay and also operating costs. In the paper, an agent-based model is proposed for support decision making in vehicle allocation. The overview of the aircrafts ground services procedures is firstly mentioned with different optimization methods suggested by researchers. Then, the agent-based approach is introduced and in the latter part of report and a multi-agent system is built and proposed which is decision supportive for CASL in optimizing the maintenance vehicles' allocation. The application provides flexibility for inputting number of different kinds of vehicles, simulation duration and aircraft arrival rate in order to simulation different scenarios which occurs in HKIA.

Improving Agent Based Models and Validation through Data Fusion.

Science.gov (United States)

Laskowski, Marek; Demianyk, Bryan C P; Friesen, Marcia R; McLeod, Robert D; Mukhi, Shamir N

2011-01-01

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level.

Dual-Function Metal-Organic Framework as a Versatile Catalyst for Detoxifying Chemical Warfare Agent Simulants.

Science.gov (United States)

Liu, Yangyang; Moon, Su-Young; Hupp, Joseph T; Farha, Omar K

2015-12-22

The nanocrystals of a porphyrin-based zirconium(IV) metal-organic framework (MOF) are used as a dual-function catalyst for the simultaneous detoxification of two chemical warfare agent simulants at room temperature. Simulants of nerve agent (such as GD, VX) and mustard gas, dimethyl 4-nitrophenyl phosphate and 2-chloroethyl ethyl sulfide, have been hydrolyzed and oxidized, respectively, to nontoxic products via a pair of pathways catalyzed by the same MOF. Phosphotriesterase-like activity of the Zr6-containing node combined with photoactivity of the porphyrin linker gives rise to a versatile MOF catalyst. In addition, bringing the MOF crystals down to the nanoregime leads to acceleration of the catalysis.

A SIMULATION-AS-A-SERVICE FRAMEWORK FACILITATING WEBGIS BASED INSTALLATION PLANNING

Directory of Open Access Journals (Sweden)

Z. Zheng

2017-09-01

Full Text Available Installation Planning is constrained by both natural and social conditions, especially for spatially sparse but functionally connected facilities. Simulation is important for proper deploy in space and configuration in function of facilities to make them a cohesive and supportive system to meet users’ operation needs. Based on requirement analysis, we propose a framework to combine GIS and Agent simulation to overcome the shortness in temporal analysis and task simulation of traditional GIS. In this framework, Agent based simulation runs as a service on the server, exposes basic simulation functions, such as scenario configuration, simulation control, and simulation data retrieval to installation planners. At the same time, the simulation service is able to utilize various kinds of geoprocessing services in Agents’ process logic to make sophisticated spatial inferences and analysis. This simulation-as-a-service framework has many potential benefits, such as easy-to-use, on-demand, shared understanding, and boosted performances. At the end, we present a preliminary implement of this concept using ArcGIS javascript api 4.0 and ArcGIS for server, showing how trip planning and driving can be carried out by agents.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

Science.gov (United States)

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

Review of the systems biology of the immune system using agent-based models.

Science.gov (United States)

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self-organisation, self-adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation-based modelling (EBM) and agent-based modelling. Owing to certain shortcomings of the EBM, agent-based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent-based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent-based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.

Agent-based simulation for human-induced hazard analysis.

Science.gov (United States)

Bulleit, William M; Drewek, Matthew W

2011-02-01

Terrorism could be treated as a hazard for design purposes. For instance, the terrorist hazard could be analyzed in a manner similar to the way that seismic hazard is handled. No matter how terrorism is dealt with in the design of systems, the need for predictions of the frequency and magnitude of the hazard will be required. And, if the human-induced hazard is to be designed for in a manner analogous to natural hazards, then the predictions should be probabilistic in nature. The model described in this article is a prototype model that used agent-based modeling (ABM) to analyze terrorist attacks. The basic approach in this article of using ABM to model human-induced hazards has been preliminarily validated in the sense that the attack magnitudes seem to be power-law distributed and attacks occur mostly in regions where high levels of wealth pass through, such as transit routes and markets. The model developed in this study indicates that ABM is a viable approach to modeling socioeconomic-based infrastructure systems for engineering design to deal with human-induced hazards. © 2010 Society for Risk Analysis.

Investigating the role of water in the Diffusion of Cholera using Agent-Based simulation

Science.gov (United States)

Augustijn, Ellen-Wien; Doldersum, Tom; Augustijn, Denie

2014-05-01

Traditionally, cholera was considered to be a waterborne disease. Currently we know that many other factors can contribute to the spread of this disease including human mobility and human behavior. However, the hydrological component in cholera diffusion is significant. The interplay between cholera and water includes bacteria (V. cholera) that survive in the aquatic environment, the possibility that run-off water from dumpsites carries the bacteria to surface water (rivers and lakes), and when the bacteria reach streams they can be carried downstream to infect new locations. Modelling is a very important tool to build theory on the interplay between different types of transmission mechanisms that together are responsible for the spread of Cholera. Agent-based simulation models are very suitable to incorporate behavior at individual level and to reproduce emergence. However, it is more difficult to incorporate the hydrological components in this type of model. In this research we present the hydrological component of an Agent-Based Cholera model developed to study a Cholera epidemic in Kumasi (Ghana) in 2005. The model was calibrated on the relative contribution of each community to the distributed pattern of cholera rather than the absolute number of incidences. Analysis of the results shows that water plays an important role in the diffusion of cholera: 75% of the cholera cases were infected via river water that was contaminated by runoff from the dumpsites. To initiate infections upstream, the probability of environment-to-human transmission seemed to be overestimated compared to what may be expected from literature. Scenario analyses show that there is a strong relation between the epidemic curve and the rainfall. Removing dumpsites that are situated close to the river resulted in a strong decrease in the number of cholera cases. Results are sensitive to the scheduling of the daily activities and the survival time of the cholera bacteria.

Proc. of the Workshop on Agent Simulation : Applications, Models, and Tools, Oct. 15-16, 1999

International Nuclear Information System (INIS)

Macal, C. M.; Sallach, D.

2000-01-01

The many motivations for employing agent-based computation in the social sciences are reviewed. It is argued that there exist three distinct uses of agent modeling techniques. One such use-the simplest-is conceptually quite close to traditional simulation in operations research. This use arises when equations can be formulated that completely describe a social process, and these equations are explicitly soluble, either analytically or numerically. In the former case, the agent model is merely a tool for presenting results, while in the latter it is a novel kind of Monte Carlo analysis. A second, more commonplace usage of computational agent models arises when mathematical models can be written down but not completely solved. In this case the agent-based model can shed significant light on the solution structure, illustrate dynamical properties of the model, serve to test the dependence of results on parameters and assumptions, and be a source of counter-examples. Finally, there are important classes of problems for which writing down equations is not a useful activity. In such circumstances, resort to agent-based computational models may be the only way available to explore such processes systematically, and constitute a third distinct usage of such models

Analyzing maintenance strategies by agent-based simulations: A feasibility study

International Nuclear Information System (INIS)

Kaegi, M.; Mock, R.; Kroeger, W.

2009-01-01

Thoroughly planned and implemented maintenance strategies save time and cost. However, the integration of maintenance work into reliability analysis is difficult as common modeling techniques are often not applicable due to state explosion which calls for restrictive model assumptions and oversimplification. From authors' point of view, agent-based modeling (ABM) of technical and organizational systems is a promising approach to overcome such problems. But since ABM is not well established in reliability analysis its feasibility in this area still has to be demonstrated. For this purpose ABM is compared with Markov chains, namely by analyzing the reliability of a maintained n-unit system with dependent repair events, applying both modeling approaches. Although ABM and Markov chains lead to the same numerical results, the former points out the potentiality of an improved system state handling. This is demonstrated by extending the ABM with operators as additional 'agents' featuring their location (x;y) availability (0;1) and different maintenance strategies. This extension highlights the capability of ABM to analyze complex emergent system behavior and allows a systematic refinement and optimization of the maintenance strategies.

A Lookahead Behavior Model for Multi-Agent Hybrid Simulation

Directory of Open Access Journals (Sweden)

Mei Yang

2017-10-01

Full Text Available In the military field, multi-agent simulation (MAS plays an important role in studying wars statistically. For a military simulation system, which involves large-scale entities and generates a very large number of interactions during the runtime, the issue of how to improve the running efficiency is of great concern for researchers. Current solutions mainly use hybrid simulation to gain fewer updates and synchronizations, where some important continuous models are maintained implicitly to keep the system dynamics, and partial resynchronization (PR is chosen as the preferable state update mechanism. However, problems, such as resynchronization interval selection and cyclic dependency, remain unsolved in PR, which easily lead to low update efficiency and infinite looping of the state update process. To address these problems, this paper proposes a lookahead behavior model (LBM to implement a PR-based hybrid simulation. In LBM, a minimal safe time window is used to predict the interactions between implicit models, upon which the resynchronization interval can be efficiently determined. Moreover, the LBM gives an estimated state value in the lookahead process so as to break the state-dependent cycle. The simulation results show that, compared with traditional mechanisms, LBM requires fewer updates and synchronizations.

Study on the E-commerce platform based on the agent

Science.gov (United States)

Fu, Ruixue; Qin, Lishuan; Gao, Yinmin

2011-10-01

To solve problem of dynamic integration in e-commerce, the Multi-Agent architecture of electronic commerce platform system based on Agent and Ontology has been introduced, which includes three major types of agent, Ontology and rule collection. In this architecture, service agent and rule are used to realize the business process reengineering, the reuse of software component, and agility of the electronic commerce platform. To illustrate the architecture, a simulation work has been done and the results imply that the architecture provides a very efficient method to design and implement the flexible, distributed, open and intelligent electronic commerce platform system to solve problem of dynamic integration in ecommerce. The objective of this paper is to illustrate the architecture of electronic commerce platform system, and the approach how Agent and Ontology support the electronic commerce platform system.

Multi-agent simulation of purchasing activities in organizations

NARCIS (Netherlands)

Ebben, Mark; de Boer, L.; Sitar-Pop, C.E.; Yucesan, E.; Chen, C.H.; Snowdon, J.L.; Charnes, J.M.

2002-01-01

In this paper we present a multi-agent simulation model to investigate purchasing activities in an organizational environment. The starting point is the observation that the majority of purchasing activities in organizations are usually performed without any involvement of the organization's

Pattern-oriented Agent-based Monte Carlo simulation of Cellular Redox Environment

DEFF Research Database (Denmark)

Tang, Jiaowei; Holcombe, Mike; Boonen, Harrie C.M.

/CYSS) and mitochondrial redox couples. Evidence suggests that both intracellular and extracellular redox can affect overall cell redox state. How redox is communicated between extracellular and intracellular environments is still a matter of debate. Some researchers conclude based on experimental data...... cells. Biochimica Et Biophysica Acta-General Subjects, 2008. 1780(11): p. 1271-1290. 5. Jones, D.P., Redox sensing: orthogonal control in cell cycle and apoptosis signalling. J Intern Med, 2010. 268(5): p. 432-48. 6. Pogson, M., et al., Formal agent-based modelling of intracellular chemical interactions...

Modeling, Simulation, and Characterization of Distributed Multi-agent Systems

Directory of Open Access Journals (Sweden)

Reed F. Young

2012-04-01

Full Text Available A strategy is described that utilizes a novel application of a potential-force function that includes the tuning of coefficients to control mobile robots orchestrated as a distributed multiagent system. Control system parameters are manipulated methodically via simulation and hardware experimentation to gain a better understanding of their impact upon mission performance of the multi-agent system as applied to a predetermined task of area exploration and mapping. Also included are descriptions of experiment infrastructure components that afford convenient solutions to research challenges. These consist of a surrogate localization (position and orientation function utilizing a novel MATLAB executable (MEX function and a user datagram protocol (UDP-based communications protocol that facilitates communication among network-based control computers.

An agent-based model for integrated emotion regulation and contagion in socially affected decision making

OpenAIRE

Manzoor, A.; Treur, J.

2015-01-01

This paper addresses an agent-based computational social agent model for the integration of emotion regulation, emotion contagion and decision making in a social context. The model integrates emotion-related valuing, in order to analyse the role of emotions in socially affected decision making. The agent-based model is illustrated for the interaction between two persons. Simulation experiments for different kinds of scenarios help to understand how decisions can be affected by regulating the ...

Simulation of Cognitive Pedestrian Agents Crowds in Crisis Situations

Directory of Open Access Journals (Sweden)

Margaret Lyell

2006-06-01

Full Text Available In crisis situations in an urban environment, first responder teams often must deal with crowds of people. Consider the case of a building fire in a dense city environment. People may be injured; walkways may be blocked, with fire equipment attempting to reach the scene. Crowd behavior can become an issue when trying to reach the injured, ensure safety and restore conditions to normal. The motivations of pedestrians that form the crowd can vary. Some are there because they are curious about the crisis situation. Others, attending to their individual concerns, may have found themselves in the 'wrong' location. They may be trying to leave the area, but the density of people as well as the spatial layout of the walkways may be impeding their progress. Other individuals, unaware of the fire, may be attempting to reach their intended destinations that happen to be near the crisis area, thus adding to crowd congestion. With a model of crowd behavior, effective strategies for resource usage in managing crowd behavior can be developed. Our approach to this problem is that of agent-based modeling and simulation. We develop a cognitive pedestrian agent model. Utilizing this model, we simulate crowd behavior in a 'city fire' scenario. Characteristics of crowd behavior with different pedestrian personality mixes and a strategy for crowd management are investigated

Agent-Based Simulation of Children’s School Travel Mode with Parental Escort Decisions

Directory of Open Access Journals (Sweden)

Peng Jing

2018-02-01

Full Text Available In the last few years, the number of private cars has expanding quickly in China, more and more parents use cars to escort their children to school, thus cause serious traffic congestions near school in many cities. In this paper, we developed an agent-based model (ABM of the parents’ choice of escort mode. The core of this model is an escort mode choice motivation adjustment function that combines distance, traffic safety and social influence. We also used ABM to exhibit the emergent decoy effect phenomenon, which is a dynamic phenomenon that the introduction of a decoy to the choice-set could increase the share of other alternatives. The model reveals the parents’ inner psychological mechanism when facing competing escort mode choice in transportation system. The simulation results show that the proportion of parents to choose bus escort was 62.45% without the decoy effect was introduced, while the proportion of parents to choose bus escort increased to 74.29% with the decoy effect was entry. The use of the ABM method gives the potential to cope with the dynamic changes in studying parent escort mode choice behavior.

On the engineering of agent-based simulations of social activities with social networks

NARCIS (Netherlands)

Ronald, N.A.; Dignum, V.; Jonker, C.; Arentze, T.A.; Timmermans, H.J.P.

2012-01-01

Context Models of how people move around cities play a role in making decisions about urban and land-use planning. Previous models have been based on space and time, and have neglected the social aspect of travel. Recent work on agent-based modelling shows promise as a new approach, especially for

Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

Directory of Open Access Journals (Sweden)

Xiangming Yao

2017-01-01

Full Text Available The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.

An agent-based approach to model land-use change at a regional scale

NARCIS (Netherlands)

Valbuena, D.F.; Verburg, P.H.; Bregt, A.K.; Ligtenberg, A.

2010-01-01

Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local

ABS-SmartComAgri: An Agent-Based Simulator of Smart Communication Protocols in Wireless Sensor Networks for Debugging in Precision Agriculture.

Science.gov (United States)

García-Magariño, Iván; Lacuesta, Raquel; Lloret, Jaime

2018-03-27

Smart communication protocols are becoming a key mechanism for improving communication performance in networks such as wireless sensor networks. However, the literature lacks mechanisms for simulating smart communication protocols in precision agriculture for decreasing production costs. In this context, the current work presents an agent-based simulator of smart communication protocols for efficiently managing pesticides. The simulator considers the needs of electric power, crop health, percentage of alive bugs and pesticide consumption. The current approach is illustrated with three different communication protocols respectively called (a) broadcast, (b) neighbor and (c) low-cost neighbor. The low-cost neighbor protocol obtained a statistically-significant reduction in the need of electric power over the neighbor protocol, with a very large difference according to the common interpretations about the Cohen's d effect size. The presented simulator is called ABS-SmartComAgri and is freely distributed as open-source from a public research data repository. It ensures the reproducibility of experiments and allows other researchers to extend the current approach.

Between Complexity and Parsimony: Can Agent-Based Modelling Resolve the Trade-off

DEFF Research Database (Denmark)

Nielsen, Helle Ørsted; Malawska, Anna Katarzyna

2013-01-01

to BR- based policy studies would be to couple research on bounded ra-tionality with agent-based modeling. Agent-based models (ABMs) are computational models for simulating the behavior and interactions of any number of decision makers in a dynamic system. Agent-based models are better suited than...... are general equilibrium models for capturing behavior patterns of complex systems. ABMs may have the potential to represent complex systems without oversimplifying them. At the same time, research in bounded rationality and behavioral economics has already yielded many insights that could inform the modeling......While Herbert Simon espoused development of general models of behavior, he also strongly advo-cated that these models be based on realistic assumptions about humans and therefore reflect the complexity of human cognition and social systems (Simon 1997). Hence, the model of bounded rationality...

Use of Agent Based Modelling to Investigate the Dynamics of Slum ...

African Journals Online (AJOL)

Urban planners and policy makers face challenges in effective management of slum ... slum characteristics using various remote sensing and artificial intelligence ... an empirically informed agent based prototype that can simulate future patterns ... The study incorporates physical, environmental, social and economic factors ...

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.

Complexity and agent-based modelling in urban research

DEFF Research Database (Denmark)

Fertner, Christian

influence on the bigger system. Traditional scientific methods or theories often tried to simplify, not accounting complex relations of actors and decision-making. The introduction of computers in simulation made new approaches in modelling, as for example agent-based modelling (ABM), possible, dealing......Urbanisation processes are results of a broad variety of actors or actor groups and their behaviour and decisions based on different experiences, knowledge, resources, values etc. The decisions done are often on a micro/individual level but resulting in macro/collective behaviour. In urban research...

A critical survey of agent-based wholesale electricity market models

International Nuclear Information System (INIS)

Weidlich, Anke; Veit, Daniel

2008-01-01

The complexity of electricity markets calls for rich and flexible modeling techniques that help to understand market dynamics and to derive advice for the design of appropriate regulatory frameworks. Agent-Based Computational Economics (ACE) is a fairly young research paradigm that offers methods for realistic electricity market modeling. A growing number of researchers have developed agent-based models for simulating electricity markets. The diversity of approaches makes it difficult to overview the field of ACE electricity research; this literature survey should guide the way through and describe the state-of-the-art of this research area. In a conclusive summary, shortcomings of existing approaches and open issues that should be addressed by ACE electricity researchers are critically discussed. (author)

Investigating immune system aging: system dynamics and agent-based modeling

OpenAIRE

Figueredo, Grazziela; Aickelin, Uwe

2010-01-01

System dynamics and agent based simulation models can\\ud both be used to model and understand interactions of entities within a population. Our modeling work presented here is concerned with understanding the suitability of the different types of simulation for the immune system aging problems and comparing their results. We are trying to answer questions such as: How fit is the immune system given a certain age? Would an immune boost be of therapeutic value, e.g. to improve the effectiveness...

An agent-based legal knowledge acquisition methodology for agile public administration

NARCIS (Netherlands)

Boer, A.; van Engers, T.

2011-01-01

This paper proposes a knowledge elicitation method based on serious gaming for theory construction about the effects of the law on the behaviours of agents. These games provide input to simulations of business process and product design alternatives. For knowledge representation, we have combined

Agent based simulation on the process of human flesh search-From perspective of knowledge and emotion

Science.gov (United States)

Zhu, Hou; Hu, Bin

2017-03-01

Human flesh search as a new net crowed behavior, on the one hand can help us to find some special information, on the other hand may lead to privacy leaking and offending human right. In order to study the mechanism of human flesh search, this paper proposes a simulation model based on agent-based model and complex networks. The computational experiments show some useful results. Discovered information quantity and involved personal ratio are highly correlated, and most of net citizens will take part in the human flesh search or will not take part in the human flesh search. Knowledge quantity does not influence involved personal ratio, but influences whether HFS can find out the target human. When the knowledge concentrates on hub nodes, the discovered information quantity is either perfect or almost zero. Emotion of net citizens influences both discovered information quantity and involved personal ratio. Concretely, when net citizens are calm to face the search topic, it will be hardly to find out the target; But when net citizens are agitated, the target will be found out easily.

Agent-based modeling and network dynamics

CERN Document Server

Namatame, Akira

2016-01-01

The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

Agent-based modeling as a tool for program design and evaluation.

Science.gov (United States)

Lawlor, Jennifer A; McGirr, Sara

2017-12-01

Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling

International Nuclear Information System (INIS)

Santos, Gabriel; Pinto, Tiago; Morais, Hugo; Sousa, Tiago M.; Pereira, Ivo F.; Fernandes, Ricardo; Praça, Isabel; Vale, Zita

2015-01-01

Highlights: • Definition of an ontology allowing the communication between multi-agents systems. • Social welfare evaluation in different electricity markets. • Demonstration of the use of the proposed ontology between two multi-agents systems. • Strategic biding in electricity markets. • European electricity markets comparison. - Abstract: The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution

"Economic microscope": The agent-based model set as an instrument in an economic system research

Science.gov (United States)

Berg, D. B.; Zvereva, O. M.; Akenov, Serik

2017-07-01

To create a valid model of a social or economic system one must consider a lot of parameters, conditions and restrictions. Systems and, consequently, the corresponding models are proved to be very complicated. The problem of such system model engineering can't be solved only with mathematical methods usage. The decision could be found in computer simulation. Simulation does not reject mathematical methods, mathematical expressions could become the foundation for a computer model. In these materials the set of agent-based computer models is under discussion. All the set models simulate productive agents communications, but every model is geared towards the specific goal, and, thus, has its own algorithm and its own peculiarities. It is shown that computer simulation can discover new features of the agents' behavior that can not be obtained by analytical solvation of mathematical equations and thus plays the role of some kind of economic microscope.

Agent-based simulation of animal behaviour

NARCIS (Netherlands)

Jonker, C.M.; Treur, J

In the biological literature on animal behaviour, in addition to real experiments and field studies, also simulation experiments are a useful source of progress. Often specific mathematical modelling techniques are adopted and directly implemented in a programming language. Modelling more complex

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

Science.gov (United States)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and

Output variability caused by random seeds in a multi-agent transport simulation model

DEFF Research Database (Denmark)

Paulsen, Mads; Rasmussen, Thomas Kjær; Nielsen, Otto Anker

2018-01-01

Dynamic transport simulators are intended to support decision makers in transport-related issues, and as such it is valuable that the random variability of their outputs is as small as possible. In this study we analyse the output variability caused by random seeds of a multi-agent transport...... simulator (MATSim) when applied to a case study of Santiago de Chile. Results based on 100 different random seeds shows that the relative accuracies of estimated link loads tend to increase with link load, but that relative errors of up to 10 % do occur even for links with large volumes. Although...

Multi-Agent System Based Special Protection and Emergency Control Scheme against Cascading Events in Power System

DEFF Research Database (Denmark)

Liu, Zhou

relay operations due to low voltage or overload state in the post stage of N-1 (or N-k) contingency. If such state could be sensed and adjusted appropriately before those relay actions, the system stability might be sustained. So it is of great significance to develop a suitable protection scheme...... the proposed protection strategy in this thesis, a real time simulation platform based on Real Time Digital Simulator (RTDS) and LabVIEW is built. In this platform, the cases of cascaded blackouts are simulated on the test system simplified from the East Denmark power system. For the MAS based control system......, the distributed power system agents are set up in RTDS, while the agents in higher level are designed by LabVIEW toolkits. The case studies and simulation results demonstrate the effectiveness of real time application of the proposed MAS based special protection and emergency control scheme against the cascaded...

Modélisation et simulation à base d'agents exemples commentés, outils informatiques et questions théoriques

CERN Document Server

Treuil, Jean-Pierre; Zucker, Jean-Daniel

2008-01-01

Cet ouvrage s'adresse aux étudiants de master des universités et aux élèves des écoles d'ingénieurs ainsi qu'aux mathématiciens, informaticiens et chercheurs de diverses disciplines qui sont amenés à créer des modèles dans leur domaine. La modélisation informatique à base d'agents permet de modéliser, à l'échelle macroscopique, des systèmes complexes à partir du comportement à l'échelle microscopique d'un grand nombre de leurs composants. L'objectif de ce livre se décline en cinq points complémentaires : Présenter au lecteur un panorama des approches de modélisation et simulation à base d'agents sous la forme de 11 exemples représentatifs puisés dans différents domaines scientifiques et technologiques. Proposer un cadre commun de définitions et une ébauche de démarche de conception qui permettent de fournir, au-delà de leur diversité apparente, une base sinon théorique du moins pratique de ces approches. Présenter les outils informatiques existants pour concevoir, spécifier...

Simulation of ethanol extractive distillation with mixed glycols as separating agent

Directory of Open Access Journals (Sweden)

I. D. Gil

2014-03-01

Full Text Available Extractive distillation is an alternative for ethanol dehydration processes that has been shown to be more effective than azeotropic distillation and, in close proximity, to be very competitive against the process that uses adsorption with molecular sieves. Glycols have been shown to be the most effective solvents in extractive distillation, mainly ethylene glycol and glycerol. In this work, an extractive distillation column was simulated with the Aspen Plus software platform, using the RadFrac module for distillation columns, to investigate the effect on the separation of the ethylene glycol-glycerol mixture composition, the separating agent feed stages, the separating agent split stream feed, and the azeotropic feed temperature. The NRTL model was used to calculate the phase equilibrium of these strongly polar mixtures. A rigorous simulation of the extractive distillation column finally established was also performed, including a secondary recovery column for the mixture of solvents and a recycle loop, to simulate an industrially relevant situation. This simulation allowed establishing the complete parameters to dehydrate ethanol: the optimal stage for separating agent feed is stage 4; the most adequate composition for the glycols mixture is 60 mol% ethylene glycol and 40 mol% glycerol. Finally, energetically efficient operating conditions for each one of the columns were established through a preliminary pinch analysis.

An Agent-Based Model of Farmer Decision Making in Jordan

Science.gov (United States)

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

2016-04-01

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

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

Science.gov (United States)

Campbell, Kenyth

2012-01-01

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

The potential of agent-based modelling for verification of people trajectories based on smartphone sensor data

International Nuclear Information System (INIS)

Hillen, F; Ehlers, M; Höfle, B; Reinartz, P

2014-01-01

In this paper the potential of smartphone sensor data for verification of people trajectories derived from airborne remote sensing data are investigated and discussed based on simulated test recordings in the city of Osnabrueck, Germany. For this purpose, the airborne imagery is simulated by images taken from a high building with a typical single lens reflex camera. The smartphone data required for the analysis of the potential is simultaneously recorded by test persons on the ground. In a second step, the quality of the smartphone sensor data is evaluated regarding the integration into simulation and modelling approaches. In this context we studied the potential of the agent-based modelling technique concerning the verification of people trajectories

Assurance in Agent-Based Systems

Energy Technology Data Exchange (ETDEWEB)

Gilliom, Laura R.; Goldsmith, Steven Y.

1999-05-10

Our vision of the future of information systems is one that includes engineered collectives of software agents which are situated in an environment over years and which increasingly improve the performance of the overall system of which they are a part. At a minimum, the movement of agent and multi-agent technology into National Security applications, including their use in information assurance, is apparent today. The use of deliberative, autonomous agents in high-consequence/high-security applications will require a commensurate level of protection and confidence in the predictability of system-level behavior. At Sandia National Laboratories, we have defined and are addressing a research agenda that integrates the surety (safety, security, and reliability) into agent-based systems at a deep level. Surety is addressed at multiple levels: The integrity of individual agents must be protected by addressing potential failure modes and vulnerabilities to malevolent threats. Providing for the surety of the collective requires attention to communications surety issues and mechanisms for identifying and working with trusted collaborators. At the highest level, using agent-based collectives within a large-scale distributed system requires the development of principled design methods to deliver the desired emergent performance or surety characteristics. This position paper will outline the research directions underway at Sandia, will discuss relevant work being performed elsewhere, and will report progress to date toward assurance in agent-based systems.

Assurance in Agent-Based Systems

International Nuclear Information System (INIS)

Gilliom, Laura R.; Goldsmith, Steven Y.

1999-01-01

Our vision of the future of information systems is one that includes engineered collectives of software agents which are situated in an environment over years and which increasingly improve the performance of the overall system of which they are a part. At a minimum, the movement of agent and multi-agent technology into National Security applications, including their use in information assurance, is apparent today. The use of deliberative, autonomous agents in high-consequence/high-security applications will require a commensurate level of protection and confidence in the predictability of system-level behavior. At Sandia National Laboratories, we have defined and are addressing a research agenda that integrates the surety (safety, security, and reliability) into agent-based systems at a deep level. Surety is addressed at multiple levels: The integrity of individual agents must be protected by addressing potential failure modes and vulnerabilities to malevolent threats. Providing for the surety of the collective requires attention to communications surety issues and mechanisms for identifying and working with trusted collaborators. At the highest level, using agent-based collectives within a large-scale distributed system requires the development of principled design methods to deliver the desired emergent performance or surety characteristics. This position paper will outline the research directions underway at Sandia, will discuss relevant work being performed elsewhere, and will report progress to date toward assurance in agent-based systems

Controlling for false negatives in agent-based models

DEFF Research Database (Denmark)

Secchi, Davide; Seri, Raffaello

2017-01-01

This article is concerned with the study of statistical power in agent-based modeling (ABM). After an overview of classic statistics theory on how to interpret Type-II error (whose occurrence is also referred to as a false negative) and power, the manuscript presents a study on ABM simulation art...... of simulation runs to reach an appropriate level of power. The study concludes with the importance for organizational behavior scholars to perform their models in an attempt to reach a power of 0.95 or higher at the 0.01 significance level....

Using Agent-Based Models in the Analysis and Forecast of Socio-Economic Development of Territories

Directory of Open Access Journals (Sweden)

Vitalii Nikolaevich Makoveev

2016-11-01

Full Text Available The purpose of the paper is to study the essence of agent-based modeling, defining its features and prospects of usage in the modeling of socio-economic development of territories and systematization of domestic and foreign approaches to the development of prototypes for agent-based models of territories. Information basis for the research comprised the works on agent-based modeling by Russian and foreign scholars, especially articles and monographs of scientists of the Central Economics and Mathematics Institute under the Russian Academy of Sciences, papers presented in an international journal The Journal of Artificial Societies and Social Simulation and other sources available on the Internet. The article presents theoretical and methodological foundations of agent-based models of territories. The author considers the concepts of “agent-based modeling” and “agent” and defines specifics of agent-based models in comparison with other types of simulation modeling. The paper also describes major stages of building agent-based models for territories and considers qualification requirements to a modeling subject. Furthermore, it reviews Russian and foreign approaches to the development of prototypes for agent-based models of territories. It has been determined that most of them deal with the modeling of spatial, territorial and socio-economic development of regions, cities and municipal entities. Agents in such models are presented by households, residents of regions and cities, enterprises and organizations operating in their territory, and public administration authorities (their inclusion in the model makes it possible to test different options of management impacts on territories by changing the model parameters, for instance, the introduction of certain prohibitions and quotas, issuance of permits, distribution of financial resources, etc.. At the end of the paper, the author formulates major conclusions. He shows the complexity faced

Agent-based modeling of sustainable behaviors

CERN Document Server

Sánchez-Maroño, Noelia; Fontenla-Romero, Oscar; Polhill, J; Craig, Tony; Bajo, Javier; Corchado, Juan

2017-01-01

Using the O.D.D. (Overview, Design concepts, Detail) protocol, this title explores the role of agent-based modeling in predicting the feasibility of various approaches to sustainability. The chapters incorporated in this volume consist of real case studies to illustrate the utility of agent-based modeling and complexity theory in discovering a path to more efficient and sustainable lifestyles. The topics covered within include: households' attitudes toward recycling, designing decision trees for representing sustainable behaviors, negotiation-based parking allocation, auction-based traffic signal control, and others. This selection of papers will be of interest to social scientists who wish to learn more about agent-based modeling as well as experts in the field of agent-based modeling.

Agent-Based Optimization

CERN Document Server

Jędrzejowicz, Piotr; Kacprzyk, Janusz

2013-01-01

This volume presents a collection of original research works by leading specialists focusing on novel and promising approaches in which the multi-agent system paradigm is used to support, enhance or replace traditional approaches to solving difficult optimization problems. The editors have invited several well-known specialists to present their solutions, tools, and models falling under the common denominator of the agent-based optimization. The book consists of eight chapters covering examples of application of the multi-agent paradigm and respective customized tools to solve  difficult optimization problems arising in different areas such as machine learning, scheduling, transportation and, more generally, distributed and cooperative problem solving.

An Individual-based Probabilistic Model for Fish Stock Simulation

Directory of Open Access Journals (Sweden)

Federico Buti

2010-08-01

Full Text Available We define an individual-based probabilistic model of a sole (Solea solea behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA, a new formalism that is introduced in the paper and that is shown to be interpretable as a Markov decision process. A given EPDTA model can be probabilistically model-checked by giving a suitable translation into syntax accepted by existing model-checkers. In order to simulate the dynamics of a given population of soles in different environmental scenarios, an agent-based simulation environment is defined in which each agent implements the behaviour of the given EPDTA model. By varying the probabilities and the characteristic functions embedded in the EPDTA model it is possible to represent different scenarios and to tune the model itself by comparing the results of the simulations with real data about the sole stock in the North Adriatic sea, available from the recent project SoleMon. The simulator is presented and made available for its adaptation to other species.

Improved identification of cranial nerves using paired-agent imaging: topical staining protocol optimization through experimentation and simulation

Science.gov (United States)

Torres, Veronica C.; Wilson, Todd; Staneviciute, Austeja; Byrne, Richard W.; Tichauer, Kenneth M.

2018-03-01

Skull base tumors are particularly difficult to visualize and access for surgeons because of the crowded environment and close proximity of vital structures, such as cranial nerves. As a result, accidental nerve damage is a significant concern and the likelihood of tumor recurrence is increased because of more conservative resections that attempt to avoid injuring these structures. In this study, a paired-agent imaging method with direct administration of fluorophores is applied to enhance cranial nerve identification. Here, a control imaging agent (ICG) accounts for non-specific uptake of the nerve-targeting agent (Oxazine 4), and ratiometric data analysis is employed to approximate binding potential (BP, a surrogate of targeted biomolecule concentration). For clinical relevance, animal experiments and simulations were conducted to identify parameters for an optimized stain and rinse protocol using the developed paired-agent method. Numerical methods were used to model the diffusive and kinetic behavior of the imaging agents in tissue, and simulation results revealed that there are various combinations of stain time and rinse number that provide improved contrast of cranial nerves, as suggested by optimal measures of BP and contrast-to-noise ratio.

Using an agent-based model to analyze the dynamic communication network of the immune response

Directory of Open Access Journals (Sweden)

Doolittle John

2011-01-01

loss outcomes. Conclusions An agent-based model capturing several key aspects of complex system dynamics was used to study the emergent properties of the immune response to viral infection. Specific patterns of interactions between leukocyte agents occurring early in the response significantly improved outcome. More interactions at later stages correlated with persistent inflammation and infection. These simulation experiments highlight the importance of commonly overlooked aspects of the immune response and provide insight into these processes at a resolution level exceeding the capabilities of current laboratory technologies.

An Evolutionary, Agent-Based Model to Aid in Computer Intrusion Detection and Prevention

National Research Council Canada - National Science Library

Shargel, Ben; Bonabeau, Eric; Budynek, Julien; Gaudiano, Paolo

2005-01-01

We have developed a realistic agent-based simulation model of hacker behavior. In the model, hacker scripts are generated using a simple but powerful hacker grammar that has the potential to cover all possible hacker scripts...

Agent-Based Modeling for Testing and Designing Novel Decentralized Command and Control System Paradigms

National Research Council Canada - National Science Library

Bonabeau, Eric; Hunt, Carl W; Gaudiano, Paolo

2003-01-01

Agent-based modeling (ABM) is a recent simulation modeling technique that consists of modeling a system from the bottom up, capturing the interactions taking place between the system's constituent units...

Flocking in Multi-Agent Systems with Multiple Virtual Leaders Based Only on Position Measurements

International Nuclear Information System (INIS)

Su Housheng

2012-01-01

Most existing flocking algorithms assume one single virtual leader and rely on information on both relative positions and relative velocities among neighboring agents. In this paper, the problem of controlling a flock of mobile autonomous agents to follow multiple virtual leaders is investigated by using only position information in the sense that agents with the same virtual leader asymptotically attain the same velocity and track the corresponding virtual leader based on only position measurements. A flocking algorithm is proposed under which every agent asymptotically attains its desired velocity, collision between agents can be avoided, and the final tight formation minimizes all agents' global potentials. A simulation example is presented to verify and illustrate the theoretical results. (general)

An agent-based model of signal transduction in bacterial chemotaxis.

Directory of Open Access Journals (Sweden)

Jameson Miller

2010-05-01

Full Text Available We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

An agent-based model of signal transduction in bacterial chemotaxis.

Science.gov (United States)

Miller, Jameson; Parker, Miles; Bourret, Robert B; Giddings, Morgan C

2010-05-13

We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

Individualism and Collectivism in Trade Agents

NARCIS (Netherlands)

Hofstede, G.J.; Jonker, C.M.; Verwaart, D.

2008-01-01

Agent-Based Modeling can contribute to the understanding of international trade processes. Models for the effects of culture and cultural differences on agent behavior are required for realistic agent-based simulation of international trade. This paper makes a step toward modeling of culture in

Memoryless cooperative graph search based on the simulated annealing algorithm

International Nuclear Information System (INIS)

Hou Jian; Yan Gang-Feng; Fan Zhen

2011-01-01

We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter—radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment. (interdisciplinary physics and related areas of science and technology)

Toward Simulating Realistic Pursuit-Evasion Using a Roadmap-Based Approach

KAUST Repository

Rodriguez, Samuel

2010-01-01

In this work, we describe an approach for modeling and simulating group behaviors for pursuit-evasion that uses a graph-based representation of the environment and integrates multi-agent simulation with roadmap-based path planning. We demonstrate the utility of this approach for a variety of scenarios including pursuit-evasion on terrains, in multi-level buildings, and in crowds. © 2010 Springer-Verlag Berlin Heidelberg.

Emergent group level navigation: an agent-based evaluation of movement patterns in a folivorous primate.

Directory of Open Access Journals (Sweden)

Tyler R Bonnell

Full Text Available The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus, testing for: the effects of memory type (Euclidian or landmark based, amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led. Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group's step length, whereas the type of memory had the highest impact on a group's path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns.

Analysis Evacuation Route for KM Zahro Express on Fire Condition using Agent Based Modeling and Fire Dynamics Simulatior

Directory of Open Access Journals (Sweden)

Trika Pitana

2017-09-01

Full Text Available Safety is the thing that needs to be preferred by users of transport, passengers should also understand about safety procedures and evacuation procedures in the means of transport. There have been many accidents that happen in the world of transport, particularly in the shipping world, from 2010 to 2016 is no more than 50 accidents of ships in accordance with the cause recorded by KNKT (Komisi Nasional Keselamatan Transportasi. On this research was discussed the evacuation time on the ship KM Zahro express that occurred earlier in the year 2017 in the Kepulauan Seribu, DKI Jakarta. Almost all passenger dead caused by fire from power source in engine room. This thesis will explaine about evacuation time and dangers from fire that interfere the process of evacuation. The methods used are Agent Based Modeling and Simulation (ABMS and Fire Dynamics Simulator (FDS for modeling fire simulation. Agent-Based Modeling software (pathfinder and Fire Dynamics Simulator software (pyrosim are used to calculate time evacuation in normal condition and fire condition of KM Zahro Express. Agent-Based Modeling and Simulator (ABMS is a modeling method that aims to model complex problems based on real cases. Agent-Based Modeling and Simulator (ABMS is designed to model a place that has a seat, path, exit door, humans, and others. Pyrosim is a graphical user interface for the Fire Dynamics Simulator (FDS. FDS models can predict smoke, temperature, carbon monoxide, and other substances during fires.  In this case the existing models can be used to plan and prepare an emergency if unwanted things happen. As well as using basic rules which refer to the Safety Of Life At Sea (SOLAS and International Maritime Organization (IMO. Result of Evacuation simulation calculation on emergency conditions (two rear exit doors will be closed that match at actually condition is 29,783 minutes (respon is not taken in this simulation, calculation results obtained from simulation of

Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis

Energy Technology Data Exchange (ETDEWEB)

May Permann

2007-03-01

Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

Energy Technology Data Exchange (ETDEWEB)

Auld, Joshua; Hope, Michael; Ley, Hubert; Sokolov, Vadim; Xu, Bo; Zhang, Kuilin

2016-03-01

This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

Consensus of heterogeneous multi-agent systems based on sampled data with a small sampling delay

International Nuclear Information System (INIS)

Wang Na; Wu Zhi-Hai; Peng Li

2014-01-01

In this paper, consensus problems of heterogeneous multi-agent systems based on sampled data with a small sampling delay are considered. First, a consensus protocol based on sampled data with a small sampling delay for heterogeneous multi-agent systems is proposed. Then, the algebra graph theory, the matrix method, the stability theory of linear systems, and some other techniques are employed to derive the necessary and sufficient conditions guaranteeing heterogeneous multi-agent systems to asymptotically achieve the stationary consensus. Finally, simulations are performed to demonstrate the correctness of the theoretical results. (interdisciplinary physics and related areas of science and technology)

A Novel Framework for Characterizing Exposure-Related Behaviors Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence (CSSSA2016)

Science.gov (United States)

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing o...

Agent-based modeling: a new approach for theory building in social psychology.

Science.gov (United States)

Smith, Eliot R; Conrey, Frederica R

2007-02-01

Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach.

Simulation of the Role of Government in Spatial Agent-Based Model

Directory of Open Access Journals (Sweden)

Viktor Ivanovich Suslov

2016-09-01

Full Text Available The paper describes the further development of an agent-based multiregional input-output model of the Russian economy. We consider the idea of incorporating the government into the model and analyze the results of experimental calculations for the conditional example of spatial economy. New agents are included into the model such as the federal and regional governments, pension fund and also the state enterprises producing public goods at the federal and regional levels. The government sets four types of taxes (personal and business income taxes, VAT and payroll taxes, ensures the provision of public goods and provides social, investment and interbudgetary transfers to households, firms and budgets. Social transfers consist of social assistance and unemployment benefits. The utility functions of households are expanded by the terms associated with national and regional public goods. The budget policy is designed in accordance with the maximization of isoelastic function of social welfare that formalizes the choice between the different concepts of social justice. The Gini index is used for the monitoring the inequality of income distribution. The results of experimental calculations present the convergence of the new version of the model to the state of quasi-equilibrium. The special attention is paid an optimal level of the taxation maximizing the social welfare function. Four variants of the optimal tax rates are defined: for three major taxes at a fixed proportion of rates and for each of the tax separately at zero rates of two other taxes. The further directions of modelling are identified, they allow to investigate the spatial development of the Russian economy taking into account the decision-making by private agents in responding to government policies.

Security Framework for Agent-Based Cloud Computing

Directory of Open Access Journals (Sweden)

K Venkateshwaran

2015-06-01

Full Text Available Agent can play a key role in bringing suitable cloud services to the customer based on their requirements. In agent based cloud computing, agent does negotiation, coordination, cooperation and collaboration on behalf of the customer to make the decisions in efficient manner. However the agent based cloud computing have some security issues like (a. addition of malicious agent in the cloud environment which could demolish the process by attacking other agents, (b. denial of service by creating flooding attacks on other involved agents. (c. Some of the exceptions in the agent interaction protocol such as Not-Understood and Cancel_Meta protocol can be misused and may lead to terminating the connection of all the other agents participating in the negotiating services. Also, this paper proposes algorithms to solve these issues to ensure that there will be no intervention of any malicious activities during the agent interaction.

Travel Agent. Occupational Simulation Kit.

Science.gov (United States)

Peterson, Wayne

This career exploration instructional booklet on the travel agent's occupation is one of several resulting from the rural southwestern Colorado CEPAC Project (Career Education Process of Attitude Change). Based on a job analysis and utilizing a programed instructional format, the following content is included: A brief description of what a travel…

An agent-based simulation of persistent inequalities in health behavior: Understanding the interdependent roles of segregation, clustering, and social influence.

Science.gov (United States)

Langellier, Brent A

2016-12-01

Health inequalities are conspicuously persistent through time and often durable even in spite of interventions. In this study, I use agent-based simulation models (ABMs) to understand how the complex interrelationships between residential segregation, social network formation, group-level preferences, and social influence may contribute to this persistence. I use a more-stylized ABM, Bubblegum Village (BV), to understand how initial inequalities in bubblegum-chewing behaviors either endure, increase, or decrease over time given group-level differences in preferences, neighborhood-level barriers or facilitators of bubblegum chewing (e.g., access to bubblegum shops), and agents' preferences for segregation, homophily, and clustering (i.e., the 'tightness' of social networks). I further use BV to understand whether segregation and social network characteristics impact whether the effects of a bubblegum-reduction intervention that is very effective in the short term are durable over time, as well as to identify intervention strategies to reduce attenuation of the intervention effects. In addition to BV, I also present results from an ABM based on the distribution and social characteristics of the population in Philadelphia, PA. This model explores similar questions to BV, but examines racial/ethnic inequalities in soda consumption based on agents' social characteristics and baseline soda consumption probabilities informed by the 2007-2010 National Health and Nutrition Examination Survey. Collectively, the models suggest that residential segregation is a fundamental process for the production and persistence of health inequalities. The other major conclusion of the study is that, for behaviors that are subject to social influence and that cluster within social groups, interventions that are randomly-targeted to individuals with 'bad' behaviors will likely experience a large degree of recidivism to pre-intervention behaviors. In contrast, interventions that target

Econophysics of agent-based models

CERN Document Server

Aoyama, Hideaki; Chakrabarti, Bikas; Chakraborti, Anirban; Ghosh, Asim

2014-01-01

The primary goal of this book is to present the research findings and conclusions of physicists, economists, mathematicians and financial engineers working in the field of "Econophysics" who have undertaken agent-based modelling, comparison with empirical studies and related investigations. Most standard economic models assume the existence of the representative agent, who is “perfectly rational” and applies the utility maximization principle when taking action. One reason for this is the desire to keep models mathematically tractable: no tools are available to economists for solving non-linear models of heterogeneous adaptive agents without explicit optimization. In contrast, multi-agent models, which originated from statistical physics considerations, allow us to go beyond the prototype theories of traditional economics involving the representative agent. This book is based on the Econophys-Kolkata VII Workshop, at which many such modelling efforts were presented. In the book, leading researchers in the...

Intelligent judgements over health risks in a spatial agent-based model.

Science.gov (United States)

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

Distributed-observer-based cooperative control for synchronization of linear discrete-time multi-agent systems.

Science.gov (United States)

Liang, Hongjing; Zhang, Huaguang; Wang, Zhanshan

2015-11-01

This paper considers output synchronization of discrete-time multi-agent systems with directed communication topologies. The directed communication graph contains a spanning tree and the exosystem as its root. Distributed observer-based consensus protocols are proposed, based on the relative outputs of neighboring agents. A multi-step algorithm is presented to construct the observer-based protocols. In light of the discrete-time algebraic Riccati equation and internal model principle, synchronization problem is completed. At last, numerical simulation is provided to verify the effectiveness of the theoretical results. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

An adaptive multi-agent-based approach to smart grids control and optimization

Energy Technology Data Exchange (ETDEWEB)

Carvalho, Marco [Florida Institute of Technology, Melbourne, FL (United States); Perez, Carlos; Granados, Adrian [Institute for Human and Machine Cognition, Ocala, FL (United States)

2012-03-15

In this paper, we describe a reinforcement learning-based approach to power management in smart grids. The scenarios we consider are smart grid settings where renewable power sources (e.g. Photovoltaic panels) have unpredictable variations in power output due, for example, to weather or cloud transient effects. Our approach builds on a multi-agent system (MAS)-based infrastructure for the monitoring and coordination of smart grid environments with renewable power sources and configurable energy storage devices (battery banks). Software agents are responsible for tracking and reporting power flow variations at different points in the grid, and to optimally coordinate the engagement of battery banks (i.e. charge/idle/discharge modes) to maintain energy requirements to end-users. Agents are able to share information and coordinate control actions through a parallel communications infrastructure, and are also capable of learning, from experience, how to improve their response strategies for different operational conditions. In this paper we describe our approach and address some of the challenges associated with the communications infrastructure for distributed coordination. We also present some preliminary results of our first simulations using the GridLAB-D simulation environment, created by the US Department of Energy (DoE) at Pacific Northwest National Laboratory (PNNL). (orig.)

Agent-based distributed hierarchical control of dc microgrid systems

DEFF Research Database (Denmark)

Meng, Lexuan; Vasquez, Juan Carlos; Guerrero, Josep M.

2014-01-01

In order to enable distributed control and management for microgrids, this paper explores the application of information consensus and local decisionmaking methods formulating an agent based distributed hierarchical control system. A droop controlled paralleled DC/DC converter system is taken as ....... Standard genetic algorithm is applied in each local control system in order to search for a global optimum. Hardware-in-Loop simulation results are shown to demonstrate the effectiveness of the method.......In order to enable distributed control and management for microgrids, this paper explores the application of information consensus and local decisionmaking methods formulating an agent based distributed hierarchical control system. A droop controlled paralleled DC/DC converter system is taken...... as a case study. The objective is to enhance the system efficiency by finding the optimal sharing ratio of load current. Virtual resistances in local control systems are taken as decision variables. Consensus algorithms are applied for global information discovery and local control systems coordination...

Bridging the gap: simulations meet knowledge bases

Science.gov (United States)

King, Gary W.; Morrison, Clayton T.; Westbrook, David L.; Cohen, Paul R.

2003-09-01

Tapir and Krill are declarative languages for specifying actions and agents, respectively, that can be executed in simulation. As such, they bridge the gap between strictly declarative knowledge bases and strictly executable code. Tapir and Krill components can be combined to produce models of activity which can answer questions about mechanisms and processes using conventional inference methods and simulation. Tapir was used in DARPA's Rapid Knowledge Formation (RKF) project to construct models of military tactics from the Army Field Manual FM3-90. These were then used to build Courses of Actions (COAs) which could be critiqued by declarative reasoning or via Monte Carlo simulation. Tapir and Krill can be read and written by non-knowledge engineers making it an excellent vehicle for Subject Matter Experts to build and critique knowledge bases.

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

Science.gov (United States)

Gurarie, David; Karl, Stephan; Zimmerman, Peter A; King, Charles H; St Pierre, Timothy G; Davis, Timothy M E

2012-01-01

Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns). We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT) studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB) communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

Directory of Open Access Journals (Sweden)

David Gurarie

Full Text Available BACKGROUND: Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns. METHODOLOGY/PRINCIPAL FINDINGS: We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. CONCLUSIONS/SIGNIFICANCE: Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

Binding of chemical warfare agent simulants as guests in a coordination cage: contributions to binding and a fluorescence-based response.

Science.gov (United States)

Taylor, Christopher G P; Piper, Jerico R; Ward, Michael D

2016-05-07

Cubic coordination cages act as competent hosts for several alkyl phosphonates used as chemical warfare agent simulants; a range of cage/guest structures have been determined, contributions to guest binding analysed, and a fluorescent response to guest binding demonstrated.

Micromotor-based on-off fluorescence detection of sarin and soman simulants.

Science.gov (United States)

Singh, Virendra V; Kaufmann, Kevin; Orozco, Jahir; Li, Jinxing; Galarnyk, Michael; Arya, Gaurav; Wang, Joseph

2015-06-30

Self-propelled micromotor-based fluorescent "On-Off" detection of nerve agents is described. The motion-based assay utilizes Si/Pt Janus micromotors coated with fluoresceinamine toward real-time "on-the-fly" field detection of sarin and soman simulants.

Agent based approach for engineering and control of micro-grids

International Nuclear Information System (INIS)

Basso, Gillian

2013-01-01

Energy management is, nowadays, a subject of uttermost importance. Indeed, we are facing growing concerns such as petroleum reserve depletion, earth global warming or power quality (e.g. avoiding blackouts during peak times). Smart grids is an attempt to solve such problems, by adding to power grids bidirectional communications and ICT capabilities in order to provide an intelligent autonomic management for the grid. This thesis focuses on the management of micro-grids thanks to multi-agent systems (MAS). Micro-grids are low-power networks, composed of small and decentralized energy producers (possibly renewable) and consumers. These networks can be connected to the main grid or islanded, this make them more complex. Due to their complexity and their geographical distribution, smart grids and micro-grids can not be easily managed by a centralized system. Distributed artificial intelligences especially MAS appear to be a solution to resolve problems related to smart grids. Firstly we defined an approach implementing feedback loops. These feedback loops exist in complex systems which can be defined with several abstraction levels. Two levels are interacting. The micro-level contains a set of agents owning behaviours that can be combined. The result of the combination impact the state of the system. The macro-level processes these influences to define a new state of the system which will impact the agents behaviours at the micro-level. This feedback loop separates behaviours on several levels. This approach is used to defined a demand and supply matching problem in micro-grid. This problem afford to manage a set of goals which currently are independently processed. Finally, an application is developed using MAS that ensures grid stability thanks to storage systems. This application was thought to be integrated to the approach detailed above. Secondly, a grid simulator id developed. This simulator allows dynamic control of devices. It is based on three main principles

Information driving force and its application in agent-based modeling

Science.gov (United States)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2018-04-01

Exploring the scientific impact of online big-data has attracted much attention of researchers from different fields in recent years. Complex financial systems are typical open systems profoundly influenced by the external information. Based on the large-scale data in the public media and stock markets, we first define an information driving force, and analyze how it affects the complex financial system. The information driving force is observed to be asymmetric in the bull and bear market states. As an application, we then propose an agent-based model driven by the information driving force. Especially, all the key parameters are determined from the empirical analysis rather than from statistical fitting of the simulation results. With our model, both the stationary properties and non-stationary dynamic behaviors are simulated. Considering the mean-field effect of the external information, we also propose a few-body model to simulate the financial market in the laboratory.

Money-Scape: A Generic Agent-Based Model of Corruption

OpenAIRE

Hokky Situngkir

2004-01-01

There has been a lot of works on corruption cases. We must think that corruption is a cultural aspect in a social life. We cannot separate the corruption with the cultural system where the corruption raised. Indonesia has been recorded to be one of the countries of the worst economic and political system on corruption case. The paper is introducing the usage of agent based simulation for analyzing the corruption specifically in Indonesia as the biggest corruption level. The model showed is na...

Three essays in agent-based macroeconomics

OpenAIRE

Canzian, Giulia

2009-01-01

The dissertation is aimed at offering an insight into the agent-based methodology and its possible application to the macroeconomic analysis. Relying on this methodology, I deal with three different issues concerning heterogeneity of economic agents, bounded rationality and interaction. Specifically, the first chapter is devoted to describe the distinctive characteristics of agent-based economics and its advantages-disadvantages. In the second chapter I propose a credit market framework c...

Numeric, Agent-based or System dynamics model? Which modeling approach is the best for vast population simulation?

Science.gov (United States)

Cimler, Richard; Tomaskova, Hana; Kuhnova, Jitka; Dolezal, Ondrej; Pscheidl, Pavel; Kuca, Kamil

2018-02-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25 % of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Agent-based modeling of the energy network for hybrid cars

International Nuclear Information System (INIS)

Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

2015-01-01

Highlights: • An approach to represent and calculate multicarrier energy networks has been developed. • It provides a modeling method based on agents, for multicarrier energy networks. • It allows the system representation on a single sheet. • Energy flows circulating in the system can be observed dynamically during simulation. • The method is technology independent. - Abstract: Studies in complex energy networks devoted to the modeling of electrical power grids, were extended in previous work, where a computational multi-layered ontology, implemented using agent-based methods, was adopted. This structure is compatible with recently introduced Multiplex Networks which using Multi-linear Algebra generalize some of classical results for single-layer networks, to multilayer networks in steady state. Static results do not assist overly in understanding dynamic networks in which the values of the variables in the nodes and edges can change suddenly, driven by events, and even where new nodes or edges may appear or disappear, also because of other events. To address this gap, a computational agent-based model is developed to extend the multi-layer and multiplex approaches. In order to demonstrate the benefits of a dynamical extension, a model of the energy network in a hybrid car is presented as a case study

Performance Evaluation of Bidding-Based Multi-Agent Scheduling Algorithms for Manufacturing Systems

Directory of Open Access Journals (Sweden)

Antonio Gordillo

2014-10-01

Full Text Available Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

Science.gov (United States)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Development of a Persistent Chemical Agent Simulator System (PCASS)

Science.gov (United States)

Mcginness, W. G.

1983-01-01

The development of a persistent chemical agent simulation system (PCASS) is described. This PCASS is to be used for the military training of troops to simulate actual chemical warfare. The purpose of this system is to facilitate in the determination of chemical contamination and effectiveness of decontamination for training purposes. The fluorescent tracer employed has no daylight activation, but yet is easily removed with a decontaminate solution or water and surfactants. Also employed is a time delayed color developing system. When an individual is subjected to the PCASS and does not decontaminate adequately, red blotches or red coloration will develop as a function of time and temperature. The intent of this is to simulate the delayed chemical reaction of mustard contaminates.

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

Directory of Open Access Journals (Sweden)

Hee-Jun Cha

2015-12-01

Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

A mathematical framework for agent based models of complex biological networks.

Science.gov (United States)

Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

2011-07-01

Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

Is the person-situation debate important for agent-based modeling and vice-versa?

Directory of Open Access Journals (Sweden)

Katarzyna Sznajd-Weron

Full Text Available Agent-based models (ABM are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not.Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks and analytic calculations (for a complete graph we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature.This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

International Nuclear Information System (INIS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-01-01

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model

Agent-based financial dynamics model from stochastic interacting epidemic system and complexity analysis

Energy Technology Data Exchange (ETDEWEB)

Lu, Yunfan, E-mail: yunfanlu@yeah.net; Wang, Jun; Niu, Hongli

2015-06-12

An agent-based financial stock price model is developed and investigated by a stochastic interacting epidemic system, which is one of the statistical physics systems and has been used to model the spread of an epidemic or a forest fire. Numerical and statistical analysis are performed on the simulated returns of the proposed financial model. Complexity properties of the financial time series are explored by calculating the correlation dimension and using the modified multiscale entropy method. In order to verify the rationality of the financial model, the real stock market indexes, Shanghai Composite Index and Shenzhen Component Index, are studied in comparison with the simulation data of the proposed model for the different infectiousness parameters. The empirical research reveals that this financial model can reproduce some important features of the real stock markets. - Highlights: • A new agent-based financial price model is developed by stochastic interacting epidemic system. • The structure of the proposed model allows to simulate the financial dynamics. • Correlation dimension and MMSE are applied to complexity analysis of financial time series. • Empirical results show the rationality of the proposed financial model.

Exploration of agent of change’s role in biodiesel energy transition process using agent-based model

Science.gov (United States)

Hidayatno, A.; Vicky, L. R.; Destyanto, A. R.

2017-11-01

As the world’s largest Crude Palm Oil (CPO) producer, Indonesia uses CPO as raw material for biodiesel. A number of policies have been designed by the Indonesian government to support adoption of biodiesel. However, the role of energy alternatives faced complex problems. Agent-based modeling can be applied to predict the impact of policies on the actors in the business process to acquire a rich discernment of the behavior and decision making by the biodiesel industries. This study evaluates government policy by attending at the adoption of the biodiesel industry in the tender run by a government with the intervention of two policy options biodiesel energy utilization by developing an agent-based model. The simulation result show that the policy of adding the biodiesel plant installed capacity has a good impact in increasing the production capacity and vendor adoption in the tender. Even so, the government should consider the cost to be incurred and the profits for vendors, so the biodiesel production targets can be successfully fulfilled.

Simulated experiment for elimination of chemical and biological warfare agents by making use of microwave plasma torch

International Nuclear Information System (INIS)

Hong, Yong C.; Kim, Jeong H.; Uhm, Han S.

2004-01-01

The threat of chemical and biological warfare agents in a domestic terrorist attack and in military conflict is increasing worldwide. Elimination and decontamination of chemical and biological warfare (CBW) agents are immediately required after such an attack. Simulated experiment for elimination of CBW agents by making use of atmospheric-pressure microwave plasma torches is carried out. Elimination of biological warfare agents indicated by the vitrification or burnout of sewage sludge powders and decomposition of toluene gas as a chemical agent stimulant are presented. A detailed characterization for the elimination of the simulant chemicals using Fourier transform infrared and gas chromatography is also presented

Simulated experiment for elimination of chemical and biological warfare agents by making use of microwave plasma torch

Science.gov (United States)

Hong, Yong C.; Kim, Jeong H.; Uhm, Han S.

2004-02-01

The threat of chemical and biological warfare agents in a domestic terrorist attack and in military conflict is increasing worldwide. Elimination and decontamination of chemical and biological warfare (CBW) agents are immediately required after such an attack. Simulated experiment for elimination of CBW agents by making use of atmospheric-pressure microwave plasma torches is carried out. Elimination of biological warfare agents indicated by the vitrification or burnout of sewage sludge powders and decomposition of toluene gas as a chemical agent stimulant are presented. A detailed characterization for the elimination of the simulant chemicals using Fourier transform infrared and gas chromatography is also presented.

Using Agent-Based Modeling to Assess Liquidity Mismatch in Open-End Bond Funds

Directory of Open Access Journals (Sweden)

Donald J. Berndt

2017-12-01

Full Text Available In this paper, we introduce a small-scale heterogeneous agent-based model of the US corporate bond market. The model includes a realistic micro-grounded ecology of investors that trade a set of bonds through dealers. Using the model, we simulate market dynamics that emerge from agent behaviors in response to basic exogenous factors (such as interest rate shocks and the introduction of regulatory policies and constraints. A first experiment focuses on the liquidity transformation provided by mutual funds and investigates the conditions under which redemption-driven bond sales may trigger market instability. We simulate the effects of increasing mutual fund market shares in the presence of market-wide repricing of risk (in the form of a 100 basis point increase in the expected returns. The simulations highlight robust-yet-fragile aspects of the growing liquidity transformation provided by mutual funds, with an inflection point beyond which redemption-driven negative feedback loops trigger market instability.

Spatial Planning and Policy Evaluation in an Urban Conurbation: a Regional Agent-Based Economic Model

Directory of Open Access Journals (Sweden)

Luzius Stricker

2017-03-01

Full Text Available This paper studies different functions and relations between 45 agglomerated municipalities in southern Switzerland (Ticino, using a territorial agent-based model. Our research adopts a bottom-up approach to urban systems, considering the agglomeration mechanism and effects of different regional and urban policies, and simulates the individual actions of diverse agents on a real city using an Agent-based model (ABM. Simulating the individual actions of diverse agents on a real city and measuring the resulting system behaviour and outcomes over time, they effectively provide a good test bed for evaluating the impact of different policies. The database is created merging the Swiss official secondary data for one reference year (2011 with Eurostat and OECD-Regpat. The results highlight that the understanding of municipalities’ functions on the territory appears to be essential for designing a solid institutional agglomeration (or city. From a methodological point of view, we contribute to improve the application of territorial ABM. Finally, our results provide a robust base to evaluate in a dynamic way various political interventions, in order to ensure a sustainable development of the agglomeration and the surrounding territories. Applying the analyses and the model on a larger scale, including further regions and conurbations, and including more indicators and variables, to obtain a more detailed and characteristic model, will constitute a further step of the research.

A Composite Agent Architecture for Multi-Agent Simulations

OpenAIRE

VanPutte, Michael; Osborn, Brian; Hiles, John

2002-01-01

CGF Computer Generated Forces and Behavioral Representation The MOVES Institute’s Computer-Generated Autonomy Group has focused on a research goal of modeling complex and adaptive behavior while at the same time making the behavior easier to create and control. This research has led to several techniques for agent construction, that includes a social and organization relationship management engine, a composite agent architecture, an agent goal apparatus, a structure for capturi...

Apports de la simulation multi-agents à l’étude des processus de diffusion

Directory of Open Access Journals (Sweden)

Eric Daudé

2004-02-01

Full Text Available Cet article présente les principaux apports d’une approche individu-centrée pour modéliser et simuler les processus de diffusion dans l’espace géographique. L’intérêt d’une telle approche est discuté au regard des limites d’une modélisation d'échelle macro-géographique traditionnellement employée pour décrire de tels phénomènes. L’équation logistique est présentée comme un exemple représentatif de cette catégorie de modèle. Les modèles de simulation à base d’agents représentent une alternative possible à une approche macro-géographique des phénomènes de diffusion. Associés aux théories de l’auto-organisation, on postule que les phénomènes observés à un certain niveau sont le résultat des nombreuses interactions qui se produisent à un ou plusieurs niveaux inférieurs. En tant qu’outil de simulation prédisposé à l’analyse de telles dynamiques, les systèmes multi-agents sont brièvement présentés. Cet article se termine par une application, la modélisation et la simulation de la diffusion d’une innovation agricole (le modèle d'Hägerstrand revisité.

A spatial web/agent-based model to support stakeholders' negotiation regarding land development.

Science.gov (United States)

Pooyandeh, Majeed; Marceau, Danielle J

2013-11-15

Decision making in land management can be greatly enhanced if the perspectives of concerned stakeholders are taken into consideration. This often implies negotiation in order to reach an agreement based on the examination of multiple alternatives. This paper describes a spatial web/agent-based modeling system that was developed to support the negotiation process of stakeholders regarding land development in southern Alberta, Canada. This system integrates a fuzzy analytic hierarchy procedure within an agent-based model in an interactive visualization environment provided through a web interface to facilitate the learning and negotiation of the stakeholders. In the pre-negotiation phase, the stakeholders compare their evaluation criteria using linguistic expressions. Due to the uncertainty and fuzzy nature of such comparisons, a fuzzy Analytic Hierarchy Process is then used to prioritize the criteria. The negotiation starts by a development plan being submitted by a user (stakeholder) through the web interface. An agent called the proposer, which represents the proposer of the plan, receives this plan and starts negotiating with all other agents. The negotiation is conducted in a step-wise manner where the agents change their attitudes by assigning a new set of weights to their criteria. If an agreement is not achieved, a new location for development is proposed by the proposer agent. This process is repeated until a location is found that satisfies all agents to a certain predefined degree. To evaluate the performance of the model, the negotiation was simulated with four agents, one of which being the proposer agent, using two hypothetical development plans. The first plan was selected randomly; the other one was chosen in an area that is of high importance to one of the agents. While the agents managed to achieve an agreement about the location of the land development after three rounds of negotiation in the first scenario, seven rounds were required in the second

Fast Conflict Resolution Based on Reinforcement Learning in Multi-agent System

Institute of Scientific and Technical Information of China (English)

PIAOSonghao; HONGBingrong; CHUHaitao

2004-01-01

In multi-agent system where each agen thas a different goal (even the team of agents has the same goal), agents must be able to resolve conflicts arising in the process of achieving their goal. Many researchers presented methods for conflict resolution, e.g., Reinforcement learning (RL), but the conventional RL requires a large computation cost because every agent must learn, at the same time the overlap of actions selected by each agent results in local conflict. Therefore in this paper, we propose a novel method to solve these problems. In order to deal with the conflict within the multi-agent system, the concept of potential field function based Action selection priority level (ASPL) is brought forward. In this method, all kinds of environment factor that may have influence on the priority are effectively computed with the potential field function. So the priority to access the local resource can be decided rapidly. By avoiding the complex coordination mechanism used in general multi-agent system, the conflict in multi-agent system is settled more efficiently. Our system consists of RL with ASPL module and generalized rules module. Using ASPL, RL module chooses a proper cooperative behavior, and generalized rule module can accelerate the learning process. By applying the proposed method to Robot Soccer, the learning process can be accelerated. The results of simulation and real experiments indicate the effectiveness of the method.

TACOP: A Cognitive Agent for a Naval Training Simulation Environment

NARCIS (Netherlands)

van Doesburg, W.A.; Verbeeck, K.; Heuvelink, A.; Tuyls, K.; Nowé, A.; van den Broek, Egon; Manderick, B.; Kuijpers, B.

2005-01-01

The full version of this paper appeared in: Doesburg, W. A. van, Heuvelink, A., and Broek, E. L. van den (2005). TACOP: A cognitive agent for a naval training simulation environment. In M. Pechoucek, D. Steiner, and S. Thompson (Eds.), Proceedings of the Industry Track of the Fourth International

A Multi Agent Based Approach for Prehospital Emergency Management.

Science.gov (United States)

Safdari, Reza; Shoshtarian Malak, Jaleh; Mohammadzadeh, Niloofar; Danesh Shahraki, Azimeh

2017-07-01

To demonstrate an architecture to automate the prehospital emergency process to categorize the specialized care according to the situation at the right time for reducing the patient mortality and morbidity. Prehospital emergency process were analyzed using existing prehospital management systems, frameworks and the extracted process were modeled using sequence diagram in Rational Rose software. System main agents were identified and modeled via component diagram, considering the main system actors and by logically dividing business functionalities, finally the conceptual architecture for prehospital emergency management was proposed. The proposed architecture was simulated using Anylogic simulation software. Anylogic Agent Model, State Chart and Process Model were used to model the system. Multi agent systems (MAS) had a great success in distributed, complex and dynamic problem solving environments, and utilizing autonomous agents provides intelligent decision making capabilities.  The proposed architecture presents prehospital management operations. The main identified agents are: EMS Center, Ambulance, Traffic Station, Healthcare Provider, Patient, Consultation Center, National Medical Record System and quality of service monitoring agent. In a critical condition like prehospital emergency we are coping with sophisticated processes like ambulance navigation health care provider and service assignment, consultation, recalling patients past medical history through a centralized EHR system and monitoring healthcare quality in a real-time manner. The main advantage of our work has been the multi agent system utilization. Our Future work will include proposed architecture implementation and evaluation of its impact on patient quality care improvement.

An Emotional Agent Model Based on Granular Computing

Directory of Open Access Journals (Sweden)

Jun Hu

2012-01-01

Full Text Available Affective computing has a very important significance for fulfilling intelligent information processing and harmonious communication between human being and computers. A new model for emotional agent is proposed in this paper to make agent have the ability of handling emotions, based on the granular computing theory and the traditional BDI agent model. Firstly, a new emotion knowledge base based on granular computing for emotion expression is presented in the model. Secondly, a new emotional reasoning algorithm based on granular computing is proposed. Thirdly, a new emotional agent model based on granular computing is presented. Finally, based on the model, an emotional agent for patient assistant in hospital is realized, experiment results show that it is efficient to handle simple emotions.

Adsorption and Desorption of Chemical Warfare Agent Simulants on Silica Surfaces with Hydrophobic Coating

International Nuclear Information System (INIS)

Park, Eun Ji; Kim, Young Dok

2013-01-01

Aim of our study is finding adsorbents suitable for pre-concentration of chemical warfare agents (CWAs). We considered Tenax, bare silica and polydimethylsiloxane (PDMS)-coated silica as adsorbents for dimethyl methylphosphonate (DMMP) and dipropylene glycol methyl ether (DPGME). Tenax showed lower thermal stability, and therefore, desorption of CWA simulants and decomposition of Tenax took place simultaneously. Silica-based adsorbents showed higher thermal stabilities than Tenax. A drawback of silica was that adsorption of CWA simulant (DMMP) was significantly reduced by pre-treatment of the adsorbents with humid air. In the case of PDMS-coated silica, influence of humidity for CWA simulant adsorption was less pronounced due to the hydrophobic nature of PDMS-coating. We propose that PDMS-coated silica can be of potential importance as adsorbent of CWAs for their pre-concentration, which can facilitate detection of these CWAs

Adsorption and Desorption of Chemical Warfare Agent Simulants on Silica Surfaces with Hydrophobic Coating

Energy Technology Data Exchange (ETDEWEB)

Park, Eun Ji; Kim, Young Dok [Sungkyunkwan Univ., Suwon (Korea, Republic of)

2013-07-15

Aim of our study is finding adsorbents suitable for pre-concentration of chemical warfare agents (CWAs). We considered Tenax, bare silica and polydimethylsiloxane (PDMS)-coated silica as adsorbents for dimethyl methylphosphonate (DMMP) and dipropylene glycol methyl ether (DPGME). Tenax showed lower thermal stability, and therefore, desorption of CWA simulants and decomposition of Tenax took place simultaneously. Silica-based adsorbents showed higher thermal stabilities than Tenax. A drawback of silica was that adsorption of CWA simulant (DMMP) was significantly reduced by pre-treatment of the adsorbents with humid air. In the case of PDMS-coated silica, influence of humidity for CWA simulant adsorption was less pronounced due to the hydrophobic nature of PDMS-coating. We propose that PDMS-coated silica can be of potential importance as adsorbent of CWAs for their pre-concentration, which can facilitate detection of these CWAs.

Simulating Land-Use Change using an Agent-Based Land Transaction Model

Science.gov (United States)

Bakker, M. M.; van Dijk, J.; Alam, S. J.

2013-12-01

In the densely populated cultural landscapes of Europe, the vast majority of all land is owned by private parties, be it farmers (the majority), nature organizations, property developers, or citizens. Therewith, the vast majority of all land-use change arises from land transactions between different owner types: successful farms expand at the expense of less successful farms, and meanwhile property developers, individual citizens, and nature organizations also actively purchase land. These land transactions are driven by specific properties of the land, by governmental policies, and by the (economic) motives of both buyers and sellers. Climate/global change can affect these drivers at various scales: at the local scale changes in hydrology can make certain land less or more desirable; at the global scale the agricultural markets will affect motives of farmers to buy or sell land; while at intermediate (e.g. provincial) scales property developers and nature conservationists may be encouraged or discouraged to purchase land. The cumulative result of all these transactions becomes manifest in changing land-use patterns, and consequent environmental responses. Within the project Climate Adaptation for Rural Areas an agent-based land-use model was developed that explores the future response of individual land users to climate change, within the context of wider global change (i.e. policy and market change). It simulates the exchange of land among farmers and between farmers and nature organizations and property developers, for a specific case study area in the east of the Netherlands. Results show that local impacts of climate change can result in a relative stagnation in the land market in waterlogged areas. Furthermore, the increase in dairying at the expense of arable cultivation - as has been observed in the area in the past - is slowing down as arable produce shows a favourable trend in the agricultural world market. Furthermore, budgets for nature managers are

An Agent-Based Dynamic Model of Politics, Fertility and Economic Development

OpenAIRE

Zining Yang

2016-01-01

In the political economy of development, government policy choices at a single point in time can dramatically affect a country's development path by impacting fertility, economic and political decisions across generations. Combining system dynamics and agent-based modeling approaches in a complex adaptive system, a simulation framework of the Politics of Fertility and Economic Development (POFED) is formalized to understand the relationship between politics, economic, and demography change at...

A Hybrid Three Layer Architecture for Fire Agent Management in Rescue Simulation Environment

Directory of Open Access Journals (Sweden)

Alborz Geramifard

2005-06-01

Full Text Available This paper presents a new architecture called FAIS for implementing intelligent agents cooperating in a special Multi Agent environment, namely the RoboCup Rescue Simulation System. This is a layered architecture which is customized for solving fire extinguishing problem. Structural decision making algorithms are combined with heuristic ones in this model, so it's a hybrid architecture.

“Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?

Directory of Open Access Journals (Sweden)

Alison Heppenstall

2016-01-01

Full Text Available Cities are complex systems, comprising of many interacting parts. How we simulate and understand causality in urban systems is continually evolving. Over the last decade the agent-based modeling (ABM paradigm has provided a new lens for understanding the effects of interactions of individuals and how through such interactions macro structures emerge, both in the social and physical environment of cities. However, such a paradigm has been hindered due to computational power and a lack of large fine scale datasets. Within the last few years we have witnessed a massive increase in computational processing power and storage, combined with the onset of Big Data. Today geographers find themselves in a data rich era. We now have access to a variety of data sources (e.g., social media, mobile phone data, etc. that tells us how, and when, individuals are using urban spaces. These data raise several questions: can we effectively use them to understand and model cities as complex entities? How well have ABM approaches lent themselves to simulating the dynamics of urban processes? What has been, or will be, the influence of Big Data on increasing our ability to understand and simulate cities? What is the appropriate level of spatial analysis and time frame to model urban phenomena? Within this paper we discuss these questions using several examples of ABM applied to urban geography to begin a dialogue about the utility of ABM for urban modeling. The arguments that the paper raises are applicable across the wider research environment where researchers are considering using this approach.

Methods for Model-Based Reasoning within Agent-Based Ambient Intelligence Applications

NARCIS (Netherlands)

Bosse, T.; Both, F.; Gerritsen, C.; Hoogendoorn, M.; Treur, J.

2012-01-01

Within agent-based Ambient Intelligence applications agents react to humans based on information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on the extent to which an agent understands the human and is able to interpret the available

The effects of residential real-time pricing contracts on transco loads, pricing, and profitability: Simulations using the N-ABLE trademark agent-based model

International Nuclear Information System (INIS)

Ehlen, Mark A.; Scholand, Andrew J.; Stamber, Kevin L.

2007-01-01

An agent-based model is constructed in which a demand aggregator sells both uniform-price and real-time price (RTP) contracts to households as means for adding price elasticity in residential power use sectors, particularly during peak-price hours of the day. Simulations suggest that RTP contracts help a demand aggregator (1) shift its long-term contracts toward off-peak hours, thereby reducing its cost of power and (2) increase its short-run profits if it is one of the first aggregators to have large numbers of RTP contracts; but (3) create susceptibilities to short-term market demand and price volatilities. (author)

Carbon emissions trading scheme exploration in China: A multi-agent-based model

International Nuclear Information System (INIS)

Tang, Ling; Wu, Jiaqian; Yu, Lean; Bao, Qin

2015-01-01

To develop a low-carbon economy, China launched seven pilot programs for carbon emissions trading (CET) in 2011 and plans to establish a nationwide CET mechanism in 2015. This paper formulated a multi-agent-based model to investigate the impacts of different CET designs in order to find the most appropriate one for China. The proposed bottom-up model includes all main economic agents in a general equilibrium framework. The simulation results indicate that (1) CET would effectively reduce carbon emissions, with a certain negative impact on the economy, (2) as for allowance allocation, the grandfathering rule is relatively moderate, while the benchmarking rule is more aggressive, (3) as for the carbon price, when the price level in the secondary CET market is regulated to be around RMB 40 per metric ton, a satisfactory emission mitigation effect can be obtained, (4) the penalty rate is suggested to be carefully designed to balance the economy development and mitigation effect, and (5) subsidy policy for energy technology improvement can effectively reduce carbon emissions without an additional negative impact on the economy. The results also indicate that the proposed novel model is a promising tool for CET policy making and analyses. -- Highlights: •A multi-agent-based model is proposed for carbon emissions trading (CET) in China. •Three agents are included: government, firms in different sectors and households. •The impacts of CET on the economy and environment in China are analyzed. •Different CET designs are simulated to find an appropriate policy for China. •Results confirm the effectiveness of the model and give helpful insights into CET design

Story telling engine based on agent interaction

OpenAIRE

Porcel, Juan Carlos

2008-01-01

Comics have been used as a programming tool for agents, giving them instructions on how to act. In this thesis I do this in reverse, I use comics to describe the actions of agents already interacting with each other to create a storytelling engine that dynamically generate stories, based on the interaction of said agents. The model for the agent behaviours is based on the improvisational puppets model of Barbara Hayes-Roth. This model is chosen due to the nature of comics themselves. Comics ...

Debugging and Event Tracing for Multi-Agent Systems, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Large-scale agent systems have become key tools in modeling and simulation tools such as NASA's Airspace Concept Evaluation System (ACES), an agent-based simulation...

A framework to specify agent-based models in geographic sciences

OpenAIRE

Grueau, Cédric; Araújo, João

2015-01-01

Agent-Based Modeling (ABM) and simulation have gained popularity in the Geographic Information Systems (GIS) domain. Despite the increasing number of models built by experts and users, it remains challenging for users to specify their models in a manner in which one can understand it. This constraint represents an inhibition to the development and acceptance of the ABM approach. In this paper, we raise the questions that need to be answered in order to cope with ABM specification issues. We r...

Discrete-Event Simulation with Agents for Modeling of Dynamic Asymmetric Threats in Maritime Security

National Research Council Canada - National Science Library

Ng, Chee W

2007-01-01

.... Discrete-event simulation (DES) was used to simulate a typical port-security, local, waterside-threat response model and to test the adaptive response of asymmetric threats in reaction to port-security procedures, while a multi-agent system (MAS...

Interbank Lending Decisions in An Economic Downturn: An Agent-Based Approach

Directory of Open Access Journals (Sweden)

Deddy P. Koesrindartoto

2012-01-01

Full Text Available Interbank lending is one mechanism that can make shock, which is accepted by one bank spread to other banks (contagion. There are several researchers that focused their research on analyzing the effect of interbank lending to systemic risk. However, there is a few research that analyzed the effect of banks’ decision maker’s behavior, especially on the bank interbank lending to the systemic risk. In this research, the author creates an agent-based  simulation of the banking system to analyze the effect of banks’ decision maker’s behavior to systemic risk in economic downturn condition. The preliminary result from this research is for an economic downturn in a long time period, the banking system with a low net worth to the asset's ratio threshold will produce more default bank than the banking system with a high net worth to the asset's ratio threshold. However, for an economic downturn in small time period, banking system which all bank in their system has the higher net worth to assets ratio threshold will have the default bank first than the banking system which has the lower net worth to the asset's ratio threshold. Keywords: agent-based simulation, banker behavior, interbank lending, economic downturn

A Secure Protocol Based on a Sedentary Agent for Mobile Agent Environments

OpenAIRE

Abdelmorhit E. Rhazi; Samuel Pierre; Hanifa Boucheneb

2007-01-01

The main challenge when deploying mobile agent environments pertains to security issues concerning mobile agents and their executive platform. This paper proposes a secure protocol which protects mobile agents against attacks from malicious hosts in these environments. Protection is based on the perfect cooperation of a sedentary agent running inside a trusted third host. Results show that the protocol detects several attacks, such as denial of service, incorrect execution and re-execution of...

Diffusion and Aggregation in an Agent Based Model of Stock Market Fluctuations

Science.gov (United States)

Castiglione, Filippo

We describe a new model to simulate the dynamic interactions between market price and the decisions of two different kind of traders. They possess spatial mobility allowing to group together to form coalitions. Each coalition follows a strategy chosen from a proportional voting ``dominated'' by a leader's decision. The interplay of both kind of agents gives rise to complex price dynamics that is consistent with the main stylized facts of financial time series. The present model incorporates many features of other known models and is meant to be the first step toward the construction of an agent-based model that uses more realistic markets rules, strategies, and information structures.

With Us or Against Us: Simulated Social Touch by Virtual Agents in a Cooperative or Competitive Setting

NARCIS (Netherlands)

Huisman, Gijs; Kolkmeier, Jan; Kolkmeier, Jan; Heylen, Dirk K.J.; Bickmore, Timothy; Marsella, Stacy; Sidner, Candance

In this paper we examine how simulated social touch by a virtual agent in a cooperative or competitive augmented reality game influences the perceived trustworthiness, warmth and politeness of the agent. Before and after the game, participants interact with two agents whereby one agent touches the

Fuzzy Constraint-Based Agent Negotiation

Institute of Scientific and Technical Information of China (English)

Menq-Wen Lin; K. Robert Lai; Ting-Jung Yu

2005-01-01

Conflicts between two or more parties arise for various reasons and perspectives. Thus, resolution of conflicts frequently relies on some form of negotiation. This paper presents a general problem-solving framework for modeling multi-issue multilateral negotiation using fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraint satisfaction problem (DFCSP). Fuzzy constrains are thus used to naturally represent each agent's desires involving imprecision and human conceptualization, particularly when lexical imprecision and subjective matters are concerned. On the other hand, based on fuzzy constraint-based problem-solving, our approach enables an agent not only to systematically relax fuzzy constraints to generate a proposal, but also to employ fuzzy similarity to select the alternative that is subject to its acceptability by the opponents. This task of problem-solving is to reach an agreement that benefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the deal more quickly since their search focuses only on the feasible solution space. An application to multilateral negotiation of a travel planning is provided to demonstrate the usefulness and effectiveness of our framework.

A Hybrid Three Layer Architecture for Fire Agent Management in Rescue Simulation Environment

Directory of Open Access Journals (Sweden)

Alborz Geramifard

2008-11-01

Full Text Available This paper presents a new architecture called FAIS for imple- menting intelligent agents cooperating in a special Multi Agent environ- ment, namely the RoboCup Rescue Simulation System. This is a layered architecture which is customized for solving fire extinguishing problem. Structural decision making algorithms are combined with heuristic ones in this model, so it's a hybrid architecture.

The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

Science.gov (United States)

Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

Agent-based land markets: Heterogeneous agents, land proces and urban land use change

NARCIS (Netherlands)

Filatova, Tatiana; Parker, Dawn C.; van der Veen, A.; Amblard, F.

2007-01-01

We construct a spatially explicit agent-based model of a bilateral land market. Heterogeneous agents form their bid and ask prices for land based on the utility that they obtain from a certain location (houte/land) and base on the state of the market (an excess of demand or supply). We underline the

A Multi-Agent-Based Intelligent Sensor and Actuator Network Design for Smart House and Home Automation

Directory of Open Access Journals (Sweden)

Fei Hu

2013-08-01

Full Text Available The smart-house technology aims to increase home automation and security with reduced energy consumption. A smart house consists of various intelligent sensors and actuators operating on different platforms with conflicting objectives. This paper proposes a multi-agent system (MAS design framework to achieve smart house automation. The novelties of this work include the developments of (1 belief, desire and intention (BDI agent behavior models; (2 a regulation policy-based multi-agent collaboration mechanism; and (3 a set of metrics for MAS performance evaluation. Simulations of case studies are performed using the Java Agent Development Environment (JADE to demonstrate the advantages of the proposed method.

Emergency First Response to a Crisis Event: A Multi-Agent Simulation Approach

National Research Council Canada - National Science Library

Roginski, Jonathan W

2006-01-01

.... This process led to the development of a multi-agent simulation methodology for emergency first response specifically applied to analyze a notional vehicle bomb attack during a festival in the Baltimore Inner Harbor...

Recent advances in agent-based complex automated negotiation

CERN Document Server

Ito, Takayuki; Zhang, Minjie; Fujita, Katsuhide; Robu, Valentin

2016-01-01

This book covers recent advances in Complex Automated Negotiations as a widely studied emerging area in the field of Autonomous Agents and Multi-Agent Systems. The book includes selected revised and extended papers from the 7th International Workshop on Agent-Based Complex Automated Negotiation (ACAN2014), which was held in Paris, France, in May 2014. The book also includes brief introductions about Agent-based Complex Automated Negotiation which are based on tutorials provided in the workshop, and brief summaries and descriptions about the ANAC'14 (Automated Negotiating Agents Competition) competition, where authors of selected finalist agents explain the strategies and the ideas used by them. The book is targeted to academic and industrial researchers in various communities of autonomous agents and multi-agent systems, such as agreement technology, mechanism design, electronic commerce, related areas, as well as graduate, undergraduate, and PhD students working in those areas or having interest in them.

Agent Based Reasoning in Multilevel Flow Modeling

DEFF Research Database (Denmark)

Lind, Morten; Zhang, Xinxin

2012-01-01

to launch the MFM Workbench into an agent based environment, which can complement disadvantages of the original software. The agent-based MFM Workbench is centered on a concept called “Blackboard System” and use an event based mechanism to arrange the reasoning tasks. This design will support the new...

An agent-based approach to financial stylized facts

Science.gov (United States)

Shimokawa, Tetsuya; Suzuki, Kyoko; Misawa, Tadanobu

2007-06-01

An important challenge of the financial theory in recent years is to construct more sophisticated models which have consistencies with as many financial stylized facts that cannot be explained by traditional models. Recently, psychological studies on decision making under uncertainty which originate in Kahneman and Tversky's research attract a lot of interest as key factors which figure out the financial stylized facts. These psychological results have been applied to the theory of investor's decision making and financial equilibrium modeling. This paper, following these behavioral financial studies, would like to propose an agent-based equilibrium model with prospect theoretical features of investors. Our goal is to point out a possibility that loss-averse feature of investors explains vast number of financial stylized facts and plays a crucial role in price formations of financial markets. Price process which is endogenously generated through our model has consistencies with, not only the equity premium puzzle and the volatility puzzle, but great kurtosis, asymmetry of return distribution, auto-correlation of return volatility, cross-correlation between return volatility and trading volume. Moreover, by using agent-based simulations, the paper also provides a rigorous explanation from the viewpoint of a lack of market liquidity to the size effect, which means that small-sized stocks enjoy excess returns compared to large-sized stocks.

An agent-based approach equipped with game theory. Strategic collaboration among learning agents during a dynamic market change in the California electricity crisis

Energy Technology Data Exchange (ETDEWEB)

Sueyoshi, Toshiyuki [Department of Management, New Mexico Institute of Mining and Technology, Socorro, NM 87801 (United States); Department of Industrial and Information Management, National Cheng Kung University, Tainan (China)

2010-09-15

An agent-based approach is a numerical (computer-intensive) method to explore the complex characteristics and dynamics of microeconomics. Using the agent-based approach, this study investigates the learning speed of traders and their strategic collaboration in a dynamic market change of electricity. An example of such a market change can be found in the California electricity crisis (2000-2001). This study incorporates the concept of partial reinforcement learning into trading agents and finds that they have two learning components: learning from a dynamic market change and learning from collaboration with other traders. The learning speed of traders becomes slow when a large fluctuation occurs in the power exchange market. The learning speed depends upon the type of traders, their learning capabilities and the fluctuation of market fundamentals. The degree of collaboration among traders gradually reduces during the electricity crisis. The strategic collaboration among traders is examined by a large simulator equipped with multiple learning capabilities. (author)

An agent-based approach equipped with game theory. Strategic collaboration among learning agents during a dynamic market change in the California electricity crisis

International Nuclear Information System (INIS)

Sueyoshi, Toshiyuki

2010-01-01

An agent-based approach is a numerical (computer-intensive) method to explore the complex characteristics and dynamics of microeconomics. Using the agent-based approach, this study investigates the learning speed of traders and their strategic collaboration in a dynamic market change of electricity. An example of such a market change can be found in the California electricity crisis (2000-2001). This study incorporates the concept of partial reinforcement learning into trading agents and finds that they have two learning components: learning from a dynamic market change and learning from collaboration with other traders. The learning speed of traders becomes slow when a large fluctuation occurs in the power exchange market. The learning speed depends upon the type of traders, their learning capabilities and the fluctuation of market fundamentals. The degree of collaboration among traders gradually reduces during the electricity crisis. The strategic collaboration among traders is examined by a large simulator equipped with multiple learning capabilities. (author)

Agent-based models of financial markets

Energy Technology Data Exchange (ETDEWEB)

Samanidou, E [Department of Economics, University of Kiel, Olshausenstrasse 40, D-24118 Kiel (Germany); Zschischang, E [HSH Nord Bank, Portfolio Mngmt. and Inv., Martensdamm 6, D-24103 Kiel (Germany); Stauffer, D [Institute for Theoretical Physics, Cologne University, D-50923 Koeln (Germany); Lux, T [Department of Economics, University of Kiel, Olshausenstrasse 40, D-24118 Kiel (Germany)

2007-03-15

This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we

Agent-based models of financial markets

Science.gov (United States)

Samanidou, E.; Zschischang, E.; Stauffer, D.; Lux, T.

2007-03-01

This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont

Agent-based models of financial markets

International Nuclear Information System (INIS)

Samanidou, E; Zschischang, E; Stauffer, D; Lux, T

2007-01-01

This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont

A GIS-Based 3D Simulation for Occupant Evacuation in a Building

Institute of Scientific and Technical Information of China (English)

TANG Fangqin; ZHANG Xin

2008-01-01

The evacuation efficiency of building plans is of obvious importance to the public safety.The cem- plexity of building plans,however,makes it difficult for the efficiency evaluation.This paper presents a com- putational model AutoEscape,which can simulate the evacuation process for any given occupant distribu. Uon in buildings.Designed as an extensible multi-level structure, the model constructs the geometry level and occupant level and establishes the interactions between levels.The GIS-based environmental analysis is realized to automatically generate the geometric representation and formulate the cognition of agents. The multi-agent based technology is employed to simulate the crowd behaviom with autonomously acting individuals.A visualization component,which provides 3D free observations for the simulation process,is developed on the platform of OGRE and integrated into the system interface in form of ActiveX control.Fi- nally,a case study has been conducted and the results have been compared with the results of an existing model to show the reliability and capacity of AutoEscape simulation.

Multi-issue Agent Negotiation Based on Fairness

Science.gov (United States)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

Utility decay rates of T1-weighted magnetic resonance imaging contrast based on redox-sensitive paramagnetic nitroxyl contrast agents

International Nuclear Information System (INIS)

Matsumoto, Ken-ichiro

2009-01-01

The availability and applicability of the combination of paramagnetic nitroxyl contrast agent and T 1 -weighted gradient echo (GE)-based dynamic magnetic resonance imaging (MRI) measurement for redox imaging are described. The time courses of T 1 -weighted GE MRI signal intensities according to first-order paramagnetic loss of a nitroxyl contrast agent were simulated for several experimental conditions. The apparent decay rate calculated based on decreasing T 1 -weighted MRI contrast (k MRI ) can show an approximate value of the original decay rate (k true ) discretionarily given for simulation with suitable experimental parameters. The difference between k MRI and k true can be sufficiently small under T 1 -weighted spoiled gradient echo (SPGR) scan conditions (repetition time=75 ms, echo time=3 ms, and flip angle=45deg), with a conventional redox-sensitive nitroxyl contrast agent, such as 4-hydroxy-2,2,6,6,-tetramethylpiperidine-N-oxyl (TEMPOL) and/or 3-carbamoyl-2,2,5,5-tetramethylpyrrolidine-N-oxyl (carbamoyl-PROXYL), and with intravenous (i.v.) doses of below 1.5 γmol/g body weight (b.w.) for mice. The results of this simulation suggest that the k MRI of nitroxyl contrast agents can be the primary index of redox status under biological conditions. (author)

A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

International Nuclear Information System (INIS)

Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram

2014-01-01

Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl 4 ). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl 4 -treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl 4 -injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into

Towards a Hybrid Agent-based Model for Mosquito Borne Disease.

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Mniszewski, S M; Manore, C A; Bryan, C; Del Valle, S Y; Roberts, D

2014-07-01

Agent-based models (ABM) are used to simulate the spread of infectious disease through a population. Detailed human movement, demography, realistic business location networks, and in-host disease progression are available in existing ABMs, such as the Epidemic Simulation System (EpiSimS). These capabilities make possible the exploration of pharmaceutical and non-pharmaceutical mitigation strategies used to inform the public health community. There is a similar need for the spread of mosquito borne pathogens due to the re-emergence of diseases such as chikungunya and dengue fever. A network-patch model for mosquito dynamics has been coupled with EpiSimS. Mosquitoes are represented as a "patch" or "cloud" associated with a location. Each patch has an ordinary differential equation (ODE) mosquito dynamics model and mosquito related parameters relevant to the location characteristics. Activities at each location can have different levels of potential exposure to mosquitoes based on whether they are inside, outside, or somewhere in-between. As a proof of concept, the hybrid network-patch model is used to simulate the spread of chikungunya through Washington, DC. Results are shown for a base case, followed by varying the probability of transmission, mosquito count, and activity exposure. We use visualization to understand the pattern of disease spread.

Chemical warfare agent simulants for human volunteer trials of emergency decontamination: A systematic review.

Science.gov (United States)

James, Thomas; Wyke, Stacey; Marczylo, Tim; Collins, Samuel; Gaulton, Tom; Foxall, Kerry; Amlôt, Richard; Duarte-Davidson, Raquel

2018-01-01

Incidents involving the release of chemical agents can pose significant risks to public health. In such an event, emergency decontamination of affected casualties may need to be undertaken to reduce injury and possible loss of life. To ensure these methods are effective, human volunteer trials (HVTs) of decontamination protocols, using simulant contaminants, have been conducted. Simulants must be used to mimic the physicochemical properties of more harmful chemicals, while remaining non-toxic at the dose applied. This review focuses on studies that employed chemical warfare agent simulants in decontamination contexts, to identify those simulants most suitable for use in HVTs of emergency decontamination. Twenty-two simulants were identified, of which 17 were determined unsuitable for use in HVTs. The remaining simulants (n = 5) were further scrutinized for potential suitability according to toxicity, physicochemical properties and similarities to their equivalent toxic counterparts. Three suitable simulants, for use in HVTs were identified; methyl salicylate (simulant for sulphur mustard), diethyl malonate (simulant for soman) and malathion (simulant for VX or toxic industrial chemicals). All have been safely used in previous HVTs, and have a range of physicochemical properties that would allow useful inference to more toxic chemicals when employed in future studies of emergency decontamination systems. © 2017 Crown Copyright. Journal of Applied Toxicology published by John Wiley & Sons, Ltd.

The contribution of agent-based simulations to conservation management on a Natura 2000 site.

Science.gov (United States)

Dupont, Hélène; Gourmelon, Françoise; Rouan, Mathias; Le Viol, Isabelle; Kerbiriou, Christian

2016-03-01

The conservation of biodiversity today must include the participation and support of local stakeholders. Natura 2000 can be considered as a conservation system that, in its application in most EU countries, relies on the participation of local stakeholders. Our study proposes a scientific method for participatory modelling, with the aim of contributing to the conservation management of habitats and species at a Natura 2000 site (Crozon Peninsula, Bretagne, France) that is representative of in landuse changes in coastal areas. We make use of companion modelling and its associated tools (scenario-planning, GIS, multi-agent modelling and simulations) to consider possible futures through the co-construction of management scenarios and the understanding of their consequences on different indicators of biodiversity status (habitats, avifauna, flora). The maintenance of human activities as they have been carried out since the creation of the Natura 2000s zone allows the biodiversity values to remain stable. Extensive agricultural activities have been shown to be essential to this maintenance, whereas management sustained by the multiplication of conservation actions brings about variable results according to the indicators. None of the scenarios has a positive incidence on the set of indicators. However, an understanding of the modelling system and the results of the simulations allow for the refining of the selection of conservation actions in relation to the species to be preserved. Copyright © 2015 Elsevier Ltd. All rights reserved.

Constructing Agent Model for Virtual Training Systems

Science.gov (United States)

Murakami, Yohei; Sugimoto, Yuki; Ishida, Toru

Constructing highly realistic agents is essential if agents are to be employed in virtual training systems. In training for collaboration based on face-to-face interaction, the generation of emotional expressions is one key. In training for guidance based on one-to-many interaction such as direction giving for evacuations, emotional expressions must be supplemented by diverse agent behaviors to make the training realistic. To reproduce diverse behavior, we characterize agents by using a various combinations of operation rules instantiated by the user operating the agent. To accomplish this goal, we introduce a user modeling method based on participatory simulations. These simulations enable us to acquire information observed by each user in the simulation and the operating history. Using these data and the domain knowledge including known operation rules, we can generate an explanation for each behavior. Moreover, the application of hypothetical reasoning, which offers consistent selection of hypotheses, to the generation of explanations allows us to use otherwise incompatible operation rules as domain knowledge. In order to validate the proposed modeling method, we apply it to the acquisition of an evacuee's model in a fire-drill experiment. We successfully acquire a subject's model corresponding to the results of an interview with the subject.

Ex Vivo Perfusion-Simulation Measurements of Microbubbles as a Scattering Contrast Agent for Grating-Based X-Ray Dark-Field Imaging.

Directory of Open Access Journals (Sweden)

Astrid Velroyen

Full Text Available The investigation of dedicated contrast agents for x-ray dark-field imaging, which exploits small-angle scattering at microstructures for contrast generation, is of strong interest in analogy to the common clinical use of high-atomic number contrast media in conventional attenuation-based imaging, since dark-field imaging has proven to provide complementary information. Therefore, agents consisting of gas bubbles, as used in ultrasound imaging for example, are of particular interest. In this work, we investigate an experimental contrast agent based on microbubbles consisting of a polyvinyl-alcohol shell with an iron oxide coating, which was originally developed for multimodal imaging and drug delivery. Its performance as a possible contrast medium for small-animal angiography was examined using a mouse carcass to realistically consider attenuating and scattering background signal. Subtraction images of dark field, phase contrast and attenuation were acquired for a concentration series of 100%, 10% and 1.3% to mimic different stages of dilution in the contrast agent in the blood vessel system. The images were compared to the gold-standard iodine-based contrast agent Solutrast, showing a good contrast improvement by microbubbles in dark-field imaging. This study proves the feasibility of microbubble-based dark-field contrast-enhancement in presence of scattering and attenuating mouse body structures like bone and fur. Therefore, it suggests a strong potential of the use of polymer-based microbubbles for small-animal dark-field angiography.

Evaluation of CO2 free electricity trading market in Japan by multi-agent simulations

International Nuclear Information System (INIS)

Sichao, Kan; Yamamoto, Hiromi; Yamaji, Kenji

2010-01-01

As of November 2008, a new market, the CO 2 free electricity market, started pilot trading within the Japan Electric Power Exchange (JEPX). The electricity in this market comes from renewable resources, nuclear or fossil thermal power with CDM credits. The demanders of the CO 2 free electricity are supposed to be the power companies with high emission rates. In this paper, we analyzed the effects of the new market by using a multi-agent based model to simulate the markets. From our simulation results, we found that the demander, under strict CO 2 emission regulations, tends to buy more electricity from the new CO 2 free market even though the price of this market is higher than that of the normal power exchange market. Suppliers with hydro or nuclear power plants only sell their electricity to the CO 2 free market, and suppliers with coal power plants also enter this market (with CDM credits). The media and peak demands in the normal market are met mainly by electricity from LNG power plants. We also compared the results from the multi-agent approach with those from the least-cost planning approach and found that the results of the two methods were similar. (author)

Agent-based simulation of reactions in the crowded and structured intracellular environment: Influence of mobility and location of the reactants

Directory of Open Access Journals (Sweden)

Lapin Alexei

2011-05-01

Full Text Available Abstract Background In this paper we apply a novel agent-based simulation method in order to model intracellular reactions in detail. The simulations are performed within a virtual cytoskeleton enriched with further crowding elements, which allows the analysis of molecular crowding effects on intracellular diffusion and reaction rates. The cytoskeleton network leads to a reduction in the mobility of molecules. Molecules can also unspecifically bind to membranes or the cytoskeleton affecting (i the fraction of unbound molecules in the cytosol and (ii furthermore reducing the mobility. Binding of molecules to intracellular structures or scaffolds can in turn lead to a microcompartmentalization of the cell. Especially the formation of enzyme complexes promoting metabolic channeling, e.g. in glycolysis, depends on the co-localization of the proteins. Results While the co-localization of enzymes leads to faster reaction rates, the reduced mobility decreases the collision rate of reactants, hence reducing the reaction rate, as expected. This effect is most prominent in diffusion limited reactions. Furthermore, anomalous diffusion can occur due to molecular crowding in the cell. In the context of diffusion controlled reactions, anomalous diffusion leads to fractal reaction kinetics. The simulation framework is used to quantify and separate the effects originating from molecular crowding or the reduced mobility of the reactants. We were able to define three factors which describe the effective reaction rate, namely f diff for the diffusion effect, f volume for the crowding, and f access for the reduced accessibility of the molecules. Conclusions Molecule distributions, reaction rate constants and structural parameters can be adjusted separately in the simulation allowing a comprehensive study of individual effects in the context of a realistic cell environment. As such, the present simulation can help to bridge the gap between in vivo and in vitro

Dynamics of bloggers’ communities: Bipartite networks from empirical data and agent-based modeling

Science.gov (United States)

Mitrović, Marija; Tadić, Bosiljka

2012-11-01

We present an analysis of the empirical data and the agent-based modeling of the emotional behavior of users on the Web portals where the user interaction is mediated by posted comments, like Blogs and Diggs. We consider the dataset of discussion-driven popular Diggs, in which all comments are screened by machine-learning emotion detection in the text, to determine positive and negative valence (attractiveness and aversiveness) of each comment. By mapping the data onto a suitable bipartite network, we perform an analysis of the network topology and the related time-series of the emotional comments. The agent-based model is then introduced to simulate the dynamics and to capture the emergence of the emotional behaviors and communities. The agents are linked to posts on a bipartite network, whose structure evolves through their actions on the posts. The emotional states (arousal and valence) of each agent fluctuate in time, subject to the current contents of the posts to which the agent is exposed. By an agent’s action on a post its current emotions are transferred to the post. The model rules and the key parameters are inferred from the considered empirical data to ensure their realistic values and mutual consistency. The model assumes that the emotional arousal over posts drives the agent’s action. The simulations are preformed for the case of constant flux of agents and the results are analyzed in full analogy with the empirical data. The main conclusions are that the emotion-driven dynamics leads to long-range temporal correlations and emergent networks with community structure, that are comparable with the ones in the empirical system of popular posts. In view of pure emotion-driven agents actions, this type of comparisons provide a quantitative measure for the role of emotions in the dynamics on real blogs. Furthermore, the model reveals the underlying mechanisms which relate the post popularity with the emotion dynamics and the prevalence of negative

AN AGENT BASED TRANSACTION PROCESSING SCHEME FOR DISCONNECTED MOBILE NODES

Directory of Open Access Journals (Sweden)

J.L. Walter Jeyakumar

2010-12-01

Full Text Available We present a mobile transaction framework in which mobile users can share data which is stored in the cache of a mobile agent. This mobile agent is a special mobile node which coordinates the sharing process. The proposed framework allows mobile affiliation work groups to be formed dynamically with a mobile agent and mobile hosts. Using short range wireless communication technology, mobile users can simultaneously access the data from the cache of the mobile agent. The data Access Manager module at the mobile agent enforces concurrency control using cache invalidation technique. This model supports disconnected mobile computing allowing mobile agent to move along with the Mobile Hosts. The proposed Transaction frame work has been simulated in Java 2 and performance of this scheme is compared with existing frame works.

TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY.

Science.gov (United States)

Somogyi, Endre; Hagar, Amit; Glazier, James A

2016-12-01

Living tissues are dynamic, heterogeneous compositions of objects , including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes . Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology ( CCOPM ) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models.

MODELLING TEMPORAL SCHEDULE OF URBAN TRAINS USING AGENT-BASED SIMULATION AND NSGA2-BASED MULTIOBJECTIVE OPTIMIZATION APPROACHES

Directory of Open Access Journals (Sweden)

M. Sahelgozin

2015-12-01

Full Text Available Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.

An Agent-Based Intervention to Assist Drivers Under Stereotype Threat: Effects of In-Vehicle Agents' Attributional Error Feedback.

Science.gov (United States)

Joo, Yeon Kyoung; Lee-Won, Roselyn J

2016-10-01

For members of a group negatively stereotyped in a domain, making mistakes can aggravate the influence of stereotype threat because negative stereotypes often blame target individuals and attribute the outcome to their lack of ability. Virtual agents offering real-time error feedback may influence performance under stereotype threat by shaping the performers' attributional perception of errors they commit. We explored this possibility with female drivers, considering the prevalence of the "women-are-bad-drivers" stereotype. Specifically, we investigated how in-vehicle voice agents offering error feedback based on responsibility attribution (internal vs. external) and outcome attribution (ability vs. effort) influence female drivers' performance under stereotype threat. In addressing this question, we conducted an experiment in a virtual driving simulation environment that provided moment-to-moment error feedback messages. Participants performed a challenging driving task and made mistakes preprogrammed to occur. Results showed that the agent's error feedback with outcome attribution moderated the stereotype threat effect on driving performance. Participants under stereotype threat had a smaller number of collisions when the errors were attributed to effort than to ability. In addition, outcome attribution feedback moderated the effect of responsibility attribution on driving performance. Implications of these findings are discussed.

Understanding agent-based models of financial markets: A bottom-up approach based on order parameters and phase diagrams

Science.gov (United States)

Lye, Ribin; Tan, James Peng Lung; Cheong, Siew Ann

2012-11-01

We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby N independent traders buy and sell M stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction fb of traders buy a random stock on offer, or a fraction fs of traders sell a random stock in their portfolio. Based on our simulations, we find that it is possible to identify useful order parameters from the steady-state price distributions of all three models. Using these order parameters as a guide, we find three phases: (i) the dead market; (ii) the boom market; and (iii) the jammed market in the phase diagram of the deterministic model. Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.

Estimation of the age-specific per-contact probability of Ebola virus transmission in Liberia using agent-based simulations

Science.gov (United States)

Siettos, Constantinos I.; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios

2016-06-01

Based on multiscale agent-based computations we estimated the per-contact probability of transmission by age of the Ebola virus disease (EVD) that swept through Liberia from May 2014 to March 2015. For the approximation of the epidemic dynamics we have developed a detailed agent-based model with small-world interactions between individuals categorized by age. For the estimation of the structure of the evolving contact network as well as the per-contact transmission probabilities by age group we exploited the so called Equation-Free framework. Model parameters were fitted to official case counts reported by the World Health Organization (WHO) as well as to recently published data of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate.

A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression

Energy Technology Data Exchange (ETDEWEB)

Dutta-Moscato, Joyeeta [Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Solovyev, Alexey [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Mathematics, University of Pittsburgh, Pittsburgh, PA (United States); Mi, Qi [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA (United States); Nishikawa, Taichiro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Soto-Gutierrez, Alejandro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Pathology, University of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Fox, Ira J. [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Vodovotz, Yoram, E-mail: vodovotzy@upmc.edu [Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States)

2014-05-30

Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl{sub 4}). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl{sub 4}-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl{sub 4}-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant

Out of the net: An agent-based model to study human movements influence on local-scale malaria transmission.

Directory of Open Access Journals (Sweden)

Francesco Pizzitutti

Full Text Available Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

Out of the net: An agent-based model to study human movements influence on local-scale malaria transmission.

Science.gov (United States)

Pizzitutti, Francesco; Pan, William; Feingold, Beth; Zaitchik, Ben; Álvarez, Carlos A; Mena, Carlos F

2018-01-01

Though malaria control initiatives have markedly reduced malaria prevalence in recent decades, global eradication is far from actuality. Recent studies show that environmental and social heterogeneities in low-transmission settings have an increased weight in shaping malaria micro-epidemiology. New integrated and more localized control strategies should be developed and tested. Here we present a set of agent-based models designed to study the influence of local scale human movements on local scale malaria transmission in a typical Amazon environment, where malaria is transmission is low and strongly connected with seasonal riverine flooding. The agent-based simulations show that the overall malaria incidence is essentially not influenced by local scale human movements. In contrast, the locations of malaria high risk spatial hotspots heavily depend on human movements because simulated malaria hotspots are mainly centered on farms, were laborers work during the day. The agent-based models are then used to test the effectiveness of two different malaria control strategies both designed to reduce local scale malaria incidence by targeting hotspots. The first control scenario consists in treat against mosquito bites people that, during the simulation, enter at least once inside hotspots revealed considering the actual sites where human individuals were infected. The second scenario involves the treatment of people entering in hotspots calculated assuming that the infection sites of every infected individual is located in the household where the individual lives. Simulations show that both considered scenarios perform better in controlling malaria than a randomized treatment, although targeting household hotspots shows slightly better performance.

Landscape Epidemiology Modeling Using an Agent-Based Model and a Geographic Information System

Directory of Open Access Journals (Sweden)

S. M. Niaz Arifin

2015-05-01

Full Text Available A landscape epidemiology modeling framework is presented which integrates the simulation outputs from an established spatial agent-based model (ABM of malaria with a geographic information system (GIS. For a study area in Kenya, five landscape scenarios are constructed with varying coverage levels of two mosquito-control interventions. For each scenario, maps are presented to show the average distributions of three output indices obtained from the results of 750 simulation runs. Hot spot analysis is performed to detect statistically significant hot spots and cold spots. Additional spatial analysis is conducted using ordinary kriging with circular semivariograms for all scenarios. The integration of epidemiological simulation-based results with spatial analyses techniques within a single modeling framework can be a valuable tool for conducting a variety of disease control activities such as exploring new biological insights, monitoring epidemiological landscape changes, and guiding resource allocation for further investigation.

Towards Agent-Based Model Specification in Smart Grid: A Cognitive Agent-based Computing Approach

OpenAIRE

Akram, Waseem; Niazi, Muaz A.; Iantovics, Laszlo Barna

2017-01-01

A smart grid can be considered as a complex network where each node represents a generation unit or a consumer. Whereas links can be used to represent transmission lines. One way to study complex systems is by using the agent-based modeling (ABM) paradigm. An ABM is a way of representing a complex system of autonomous agents interacting with each other. Previously, a number of studies have been presented in the smart grid domain making use of the ABM paradigm. However, to the best of our know...

The dynamic influence of human resources on evidence-based intervention sustainability and population outcomes: an agent-based modeling approach.

Science.gov (United States)

McKay, Virginia R; Hoffer, Lee D; Combs, Todd B; Margaret Dolcini, M

2018-06-05

Sustaining evidence-based interventions (EBIs) is an ongoing challenge for dissemination and implementation science in public health and social services. Characterizing the relationship among human resource capacity within an agency and subsequent population outcomes is an important step to improving our understanding of how EBIs are sustained. Although human resource capacity and population outcomes are theoretically related, examining them over time within real-world experiments is difficult. Simulation approaches, especially agent-based models, offer advantages that complement existing methods. We used an agent-based model to examine the relationships among human resources, EBI delivery, and population outcomes by simulating provision of an EBI through a hypothetical agency and its staff. We used data from existing studies examining a widely implemented HIV prevention intervention to inform simulation design, calibration, and validity. Once we developed a baseline model, we used the model as a simulated laboratory by systematically varying three human resource variables: the number of staff positions, the staff turnover rate, and timing in training. We tracked the subsequent influence on EBI delivery and the level of population risk over time to describe the overall and dynamic relationships among these variables. Higher overall levels of human resource capacity at an agency (more positions) led to more extensive EBI delivery over time and lowered population risk earlier in time. In simulations representing the typical human resource investments, substantial influences on population risk were visible after approximately 2 years and peaked around 4 years. Human resources, especially staff positions, have an important impact on EBI sustainability and ultimately population health. A minimum level of human resources based on the context (e.g., size of the initial population and characteristics of the EBI) is likely needed for an EBI to have a meaningful impact on

E-laboratories : agent-based modeling of electricity markets

International Nuclear Information System (INIS)

North, M.; Conzelmann, G.; Koritarov, V.; Macal, C.; Thimmapuram, P.; Veselka, T.

2002-01-01

Electricity markets are complex adaptive systems that operate under a wide range of rules that span a variety of time scales. These rules are imposed both from above by society and below by physics. Many electricity markets are undergoing or are about to undergo a transition from centrally regulated systems to decentralized markets. Furthermore, several electricity markets have recently undergone this transition with extremely unsatisfactory results, most notably in California. These high stakes transitions require the introduction of largely untested regulatory structures. Suitable laboratories that can be used to test regulatory structures before they are applied to real systems are needed. Agent-based models can provide such electronic laboratories or ''e-laboratories.'' To better understand the requirements of an electricity market e-laboratory, a live electricity market simulation was created. This experience helped to shape the development of the Electricity Market Complex Adaptive Systems (EMCAS) model. To explore EMCAS' potential as an e-laboratory, several variations of the live simulation were created. These variations probed the possible effects of changing power plant outages and price setting rules on electricity market prices

Novel insights in agent-based complex automated negotiation

CERN Document Server

Lopez-Carmona, Miguel; Ito, Takayuki; Zhang, Minjie; Bai, Quan; Fujita, Katsuhide

2014-01-01

This book focuses on all aspects of complex automated negotiations, which are studied in the field of autonomous agents and multi-agent systems. This book consists of two parts. I: Agent-Based Complex Automated Negotiations, and II: Automated Negotiation Agents Competition. The chapters in Part I are extended versions of papers presented at the 2012 international workshop on Agent-Based Complex Automated Negotiation (ACAN), after peer reviews by three Program Committee members. Part II examines in detail ANAC 2012 (The Third Automated Negotiating Agents Competition), in which automated agents that have different negotiation strategies and are implemented by different developers are automatically negotiated in the several negotiation domains. ANAC is an international competition in which automated negotiation strategies, submitted by a number of universities and research institutes across the world, are evaluated in tournament style. The purpose of the competition is to steer the research in the area of bilate...

Multi-agent modeling for the simulation of a simple smart microgrid

International Nuclear Information System (INIS)

Kremers, Enrique; Gonzalez de Durana, Jose; Barambones, Oscar

2013-01-01

Highlights: • We created a systemic modular model for a microgrid with a load flow calculation. • The model is modular and besides the power devices includes also a communication layer. • An agent-based approach allows to include intelligent strategies on every node of the system. • First feasibility simulations were run to show the possible outcomes of generator and load management strategies. - Abstract: The smart grid is a highly complex system that is being formed from the traditional power grid, adding new and sophisticated communication and control devices. This will enable integrating new elements for distributed power generation and also achieving an increasingly automated operation so for actions of the utilities as for customers. In order to model such systems, a bottom-up method is followed, using only a few basic elements which are structured into two layers: a physical layer for the electrical power transmission and one logical layer for element communication. A simple case study is presented to analyze the possibilities of simulation. It shows a microgrid model with dynamic load management and an integrated approach that can process both electrical and communication flows

An Agent-Based Assessment of Land Use and Ecosystem Changes in Traditional Agricultural Landscape of Portugal

NARCIS (Netherlands)

Acosta, L.; Rounsevell, M.D.A.; Bakker, M.M.; Doorn, van A.M.; Gómez-Delgado, M.; Delgado, M.

2014-01-01

This paper presents an assessment of land use changes and their impacts on the ecosystem in the Montado, a traditional agricultural landscape of Portugal in response to global environmental change. The assessment uses an agent- based model (ABM) of the adaptive decisions of farmers to simulate the

9th KES Conference on Agent and Multi-Agent Systems : Technologies and Applications

CERN Document Server

Howlett, Robert; Jain, Lakhmi

2015-01-01

Agents and multi-agent systems are related to a modern software paradigm which has long been recognized as a promising technology for constructing autonomous, complex and intelligent systems. The topics covered in this volume include agent-oriented software engineering, agent co-operation, co-ordination, negotiation, organization and communication, distributed problem solving, specification of agent communication languages, agent privacy, safety and security, formalization of ontologies and conversational agents. The volume highlights new trends and challenges in agent and multi-agent research and includes 38 papers classified in the following specific topics: learning paradigms, agent-based modeling and simulation, business model innovation and disruptive technologies, anthropic-oriented computing, serious games and business intelligence, design and implementation of intelligent agents and multi-agent systems, digital economy, and advances in networked virtual enterprises. Published p...

Agent-Based Data Integration Framework

Directory of Open Access Journals (Sweden)

Łukasz Faber

2014-01-01

Full Text Available Combining data from diverse, heterogeneous sources while facilitating a unified access to it is an important (albeit difficult task. There are various possibilities of performing it. In this publication, we propose and describe an agent-based framework dedicated to acquiring and processing distributed, heterogeneous data collected from diverse sources (e.g., the Internet, external software, relational, and document databases. Using this multi-agent-based approach in the aspects of the general architecture (the organization and management of the framework, we create a proof-of-concept implementation. The approach is presented using a sample scenario in which the system is used to search for personal and professional profiles of scientists.

Mesoscopic effects in an agent-based bargaining model in regular lattices.

Science.gov (United States)

Poza, David J; Santos, José I; Galán, José M; López-Paredes, Adolfo

2011-03-09

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.

Mesoscopic effects in an agent-based bargaining model in regular lattices.

Directory of Open Access Journals (Sweden)

David J Poza

Full Text Available The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.

An Interactive Tool for Creating Multi-Agent Systems and Interactive Agent-based Games

DEFF Research Database (Denmark)

Lund, Henrik Hautop; Pagliarini, Luigi

2011-01-01

Utilizing principles from parallel and distributed processing combined with inspiration from modular robotics, we developed the modular interactive tiles. As an educational tool, the modular interactive tiles facilitate the learning of multi-agent systems and interactive agent-based games...

Linking agent-based models and stochastic models of financial markets.

Science.gov (United States)

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

A Polyoxoniobate-Polyoxovanadate Double-Anion Catalyst for Simultaneous Oxidative and Hydrolytic Decontamination of Chemical Warfare Agent Simulants.

Science.gov (United States)

Dong, Jing; Hu, Jufang; Chi, Yingnan; Lin, Zhengguo; Zou, Bo; Yang, Song; Hill, Craig L; Hu, Changwen

2017-04-10

A novel double-anion complex, H 13 [(CH 3 ) 4 N] 12 [PNb 12 O 40 (V V O) 2 ⋅(V IV 4 O 12 ) 2 ]⋅22 H 2 O (1), based on bicapped polyoxoniobate and tetranuclear polyoxovanadate was synthesized, characterized by routine techniques and used in the catalytic decontamination of chemical warfare agents. Under mild conditions, 1 catalyzes both hydrolysis of the nerve agent simulant, diethyl cyanophosphonate (DECP) and selective oxidation of the sulfur mustard simulant, 2-chloroethyl ethyl sulfide (CEES). In the oxidative decontamination system 100 % CEES was transformed selectively to nontoxic 2-chloroethyl ethyl sulfoxide and vinyl ethyl sulfoxide using nearly stoichiometric 3 % aqueous H 2 O 2 with a turnover frequency (TOF) of 16 000 h -1 . Importantly, the catalytic activity is maintained even after ten recycles and CEES is completely decontaminated in 3 mins without formation of the highly toxic sulfone by-product. A three-step oxidative mechanism is proposed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Study of the attractor structure of an agent-based sociological model

Energy Technology Data Exchange (ETDEWEB)

Timpanaro, Andre M; Prado, Carmen P C, E-mail: timpa@if.usp.br, E-mail: prado@if.usp.br [Instituto de Fisica da Universidade de Sao Paulo, Sao Paulo (Brazil)

2011-03-01

The Sznajd model is a sociophysics model that is based in the Potts model, and used for describing opinion propagation in a society. It employs an agent-based approach and interaction rules favouring pairs of agreeing agents. It has been successfully employed in modeling some properties and scale features of both proportional and majority elections (see for instance the works of A. T. Bernardes and R. N. Costa Filho), but its stationary states are always consensus states. In order to explain more complicated behaviours, we have modified the bounded confidence idea (introduced before in other opinion models, like the Deffuant model), with the introduction of prejudices and biases (we called this modification confidence rules), and have adapted it to the discrete Sznajd model. This generalized Sznajd model is able to reproduce almost all of the previous versions of the Sznajd model, by using appropriate choices of parameters. We solved the attractor structure of the resulting model in a mean-field approach and made Monte Carlo simulations in a Barabasi-Albert network. These simulations show great similarities with the mean-field, for the tested cases of 3 and 4 opinions. The dynamical systems approach that we devised allows for a deeper understanding of the potential of the Sznajd model as an opinion propagation model and can be easily extended to other models, like the voter model. Our modification of the bounded confidence rule can also be readily applied to other opinion propagation models.

Face, Content, and Construct Validations of Endoscopic Needle Injection Simulator for Transurethral Bulking Agent in Treatment of Stress Urinary Incontinence.

Science.gov (United States)

Farhan, Bilal; Soltani, Tandis; Do, Rebecca; Perez, Claudia; Choi, Hanul; Ghoniem, Gamal

2018-05-02

Endoscopic injection of urethral bulking agents is an office procedure that is used to treat stress urinary incontinence secondary to internal sphincteric deficiency. Validation studies important part of simulator evaluation and is considered important step to establish the effectiveness of simulation-based training. The endoscopic needle injection (ENI) simulator has not been formally validated, although it has been used widely at University of California, Irvine. We aimed to assess the face, content, and construct validity of the UC, Irvine ENI simulator. Dissected female porcine bladders were mounted in a modified Hysteroscopy Diagnostic Trainer. Using routine endoscopic equipment for this procedure with video monitoring, 6 urologists (experts group) and 6 urology trainee (novice group) completed urethral bulking agents injections on a total of 12 bladders using ENI simulator. Face and content validities were assessed by using structured quantitative survey which rating the realism. Construct validity was assessed by comparing the performance, time of the procedure, and the occlusive (anatomical and functional) evaluations between the experts and novices. Trainees also completed a postprocedure feedback survey. Effective injections were evaluated by measuring the retrograde urethral opening pressure, visual cystoscopic coaptation, and postprocedure gross anatomic examination. All 12 participants felt the simulator was a good training tool and should be used as essential part of urology training (face validity). ENI simulator showed good face and content validity with average score varies between the experts and the novices was 3.9/5 and 3.8/5, respectively. Content validity evaluation showed that most aspects of the simulator were adequately realistic (mean Likert scores 3.9-3.8/5). However, the bladder does not bleed, and sometimes thin. Experts significantly outperformed novices (p ENI simulator shows face, content and construct validities, although few

Using data-driven agent-based models for forecasting emerging infectious diseases

Directory of Open Access Journals (Sweden)

Srinivasan Venkatramanan

2018-03-01

Full Text Available Producing timely, well-informed and reliable forecasts for an ongoing epidemic of an emerging infectious disease is a huge challenge. Epidemiologists and policy makers have to deal with poor data quality, limited understanding of the disease dynamics, rapidly changing social environment and the uncertainty on effects of various interventions in place. Under this setting, detailed computational models provide a comprehensive framework for integrating diverse data sources into a well-defined model of disease dynamics and social behavior, potentially leading to better understanding and actions. In this paper, we describe one such agent-based model framework developed for forecasting the 2014–2015 Ebola epidemic in Liberia, and subsequently used during the Ebola forecasting challenge. We describe the various components of the model, the calibration process and summarize the forecast performance across scenarios of the challenge. We conclude by highlighting how such a data-driven approach can be refined and adapted for future epidemics, and share the lessons learned over the course of the challenge. Keywords: Emerging infectious diseases, Agent-based models, Simulation optimization, Bayesian calibration, Ebola

Validation of Agent Based Distillation Movement Algorithms

National Research Council Canada - National Science Library

Gill, Andrew

2003-01-01

Agent based distillations (ABD) are low-resolution abstract models, which can be used to explore questions associated with land combat operations in a short period of time Movement of agents within the EINSTein and MANA ABDs...

Modeling the 2014 Ebola Virus Epidemic - Agent-Based Simulations, Temporal Analysis and Future Predictions for Liberia and Sierra Leone.

Science.gov (United States)

Siettos, Constantinos; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios

2015-03-09

We developed an agent-based model to investigate the epidemic dynamics of Ebola virus disease (EVD) in Liberia and Sierra Leone from May 27 to December 21, 2014. The dynamics of the agent-based simulator evolve on small-world transmission networks of sizes equal to the population of each country, with adjustable densities to account for the effects of public health intervention policies and individual behavioral responses to the evolving epidemic. Based on time series of the official case counts from the World Health Organization (WHO), we provide estimates for key epidemiological variables by employing the so-called Equation-Free approach. The underlying transmission networks were characterized by rather random structures in the two countries with densities decreasing by ~19% from the early (May 27-early August) to the last period (mid October-December 21). Our estimates for the values of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate, are very close to the ones reported by the WHO Ebola response team during the early period of the epidemic (until September 14) that were calculated based on clinical data. Specifically, regarding the effective reproductive number Re, our analysis suggests that until mid October, Re was above 2.3 in both countries; from mid October to December 21, Re dropped well below unity in Liberia, indicating a saturation of the epidemic, while in Sierra Leone it was around 1.9, indicating an ongoing epidemic. Accordingly, a ten-week projection from December 21 estimated that the epidemic will fade out in Liberia in early March; in contrast, our results flashed a note of caution for Sierra Leone since the cumulative number of cases could reach as high as 18,000, and the number of deaths might exceed 5,000, by early March 2015. However, by processing the reported data of the very last period (December 21, 2014-January 18, 2015), we obtained more optimistic estimates indicative of a remission of

New Trends in Agent-Based Complex Automated Negotiations

CERN Document Server

Zhang, Minjie; Robu, Valentin; Fatima, Shaheen; Matsuo, Tokuro

2012-01-01

Complex Automated Negotiations represent an important, emerging area in the field of Autonomous Agents and Multi-Agent Systems. Automated negotiations can be complex, since there are a lot of factors that characterize such negotiations. These factors include the number of issues, dependencies between these issues,  representation of utilities, the negotiation protocol, the number of parties in the negotiation (bilateral or multi-party), time constraints, etc. Software agents can support automation or simulation of such complex negotiations on the behalf of their owners, and can provide them with efficient bargaining strategies. To realize such a complex automated negotiation, we have to incorporate advanced Artificial Intelligence technologies includes search, CSP, graphical utility models, Bayes nets, auctions, utility graphs, predicting and learning methods. Applications could include e-commerce tools, decision-making support tools, negotiation support tools, collaboration tools, etc. This book aims to pro...

An Active Learning Exercise for Introducing Agent-Based Modeling

Science.gov (United States)

Pinder, Jonathan P.

2013-01-01

Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

The application of neutral network integrated with genetic algorithm and simulated annealing for the simulation of rare earths separation processes by the solvent extraction technique using EHEHPA agent

International Nuclear Information System (INIS)

Tran Ngoc Ha; Pham Thi Hong Ha

2003-01-01

In the present work, neutral network has been used for mathematically modeling equilibrium data of the mixture of two rare earth elements, namely Nd and Pr with PC88A agent. Thermo-genetic algorithm based on the idea of the genetic algorithm and the simulated annealing algorithm have been used in the training procedure of the neutral networks, giving better result in comparison with the traditional modeling approach. The obtained neutral network modeling the experimental data is further used in the computer program to simulate the solvent extraction process of two elements Nd and Pr. Based on this computer program, various optional schemes for the separation of Nd and Pr have been investigated and proposed. (author)

Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems research.

Science.gov (United States)

Liu, Shiyong; Triantis, Konstantinos P; Zhao, Li; Wang, Youfa

2018-01-01

In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data

Goal-based communication using BDI agents as virtual humans in training: An ontology driven dialogue system

NARCIS (Netherlands)

Oijen, J. van; Doesburg, W. van; Dignum, F.

2011-01-01

Simulations for training can greatly benefit from BDI agents as virtual humans playing the role of key players. Learning to communicate effectively is a key aspect of training to command a team that is managing a crisis. In this paper, we present a goal-based dialogue system which has been applied

Thermodynamic and Mechanical Properties of Epon 862 With Curing Agent Detda by Molecular Simulation

National Research Council Canada - National Science Library

Tack, Jeremy L

2006-01-01

Fully atomistic molecular dynamics (MD) simulations were used to predict the properties of EPON 862 cross-linked with curing agent DETDA, a potentially useful epoxy resin for future applications of nanocomposites...

Consentaneous agent-based and stochastic model of the financial markets.

Science.gov (United States)

Gontis, Vygintas; Kononovicius, Aleksejus

2014-01-01

We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation.

Modelling of robotic work cells using agent based-approach

Science.gov (United States)

Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

2016-08-01

In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.