Dynamic Learning in Human Decision Behavior for Evacuation Scenarios under BDI Framework Seungho Lee, Young-Jun Son. 2009 INFORMS at University of Warwick, June 25-27, Coventry, U.K.

A novel approach to represent learning in human decision behavior for evacuation scenarios is proposed under the context of an extended Belief-Desire-Intention framework. In particular, we focus on how a human adjusts his perception process (involving a Bayesian belief network) in Belief Module dynamically against his performance in predicting the environment as part of his decision planning function. To this end, a Q-learning algorithm (reinforcement learning algorithm) is employed and further developed.
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The Impact of Human Decision Makers’ Individualities on The Wholesale Price Contract’s Efficiency: Simulating The Newsvendor Problem Stavrianna Dimitriou, Stewart Robinson, Kathy Kotiadis. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Suppliers and retailers in the newsvendor setting need to submit their pricing and inventory decisions respectively, well before actual customer demand is realized. In the literature they have both been typically considered as perfectly rational optimizers, exclusively interested in their own respective benefits. Under the above set of conditions the wholesale price-only contract has long been analytically proven as inefficient.
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Hybrid Simulation and Optimization-Based Capacity Planner for Integrated Photovoltaic Generation with Storage Units Esfandyar M. Mazhari. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control difficult and requires storage units. The goal of this research is to develop a flexible capacity planning tool, which will allow us to obtain a most economical mixture of capacities from solar generation as well as storage while meeting reliability requirements against fluctuating demand and weather conditions. The tool is based on hybrid (system dynamics and agent-based models) simulation and meta-heuristic optimization.
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Agent-based Modeling and Simulation Charles M. Macal, Michael J. North. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, mitigating the threat of bio-warfare, and understanding the factors that may be responsible for the fall of ancient civilizations.
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AnyLogic 4.0: Simulating Hybrid Systems with Extended UML-RT Andrei Borshchev. Simulation News Europe, No. 31 April 2001, pp 15-16

We outline a modelling approach aimed to capture sophisticated interdependencies of discrete and continuous behaviors in hybrid systems. The approach is essentially a hybrid extension of widely recognized object-oriented languages UML and UML-RT. It is fully supported by a new simulation tool AnyLogic 4.0 from Experimental Object Technologies.
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Decision Support Tool — Supply Chain Christian Wartha, Momtchil Peev, Andrei Borshchev, and Alexei Filippov. 2002 Winter Simulation Conference (WSC’02), December 8-11, 2002, San Diego, California, USA

We present a currently developed Decision Support Tool - Supply Chain (DST-SC). This is specialized domain oriented tool, which is an extension of the general purpose, UML-RT Hybrid Simulation kernel of AnyLogic by XJ Technologies. DST-SC allows high degree of flexibility with respect to the supply chain functionality being modeled, has the ability to handle large complex problems, and offers highly reusable model components, offering at the same time ease of use by non-experts in simulation.
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A Modern Simulation Approach for Pharmaceutical Portfolio Management Kirk Solo and Mark Paich. International Conference on Health Sciences Simulation (ICHSS'04), January 18 - 21, 2004, San Diego, California, USA

By creating an integrated simulation environment that models the underlying structure of a pharmaceutical enterprise portfolio it becomes possible to identify the optimal longitudinal allocation of finite resources across the constellation of available investment opportunities. The implementation of a hybrid approach that integrates multiple modeling techniques and analytic disciplines allows for a comprehensive environment that captures the underlying dynamics that drive observed market behavior. The implementation of an object oriented model structure constrains the models complexity by supporting dynamic re-use of both structure and logic.
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Agent Modeling of Hispanic Population Acculturation and Behavior Lyle Wallis, Mark Paich, and Andrei Borshchev. The 3rd International Conference on Systems Thinking in Management (ICSTM 2004), May 19 - 21, 2004, Philadelphia, Pennsylvania, USA

In recent US Census data widely reported in the press “Hispanics” have become the largest minority group in the US. Using simulation modeling technology we look at some of the structural forces that shape the characteristics of the Hispanic population. The model creates a simulated Hispanic population whose level of acculturation to the broader population of which it is a part dynamically varies according to individual choice. The modeling technique used draws on both System Dynamic and Agent based paradigms both supported by innovative AnyLogic software. The representative Hispanic population is disaggregated down to the individual level as individual agents. Each agent makes choices stochastically as modulated by its current state and the outside environment that it is in.
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Geographically-Enhanced Mathematical Models of HIV Dynamics Bobashev G.V., Zule W., Root E.D., Wechsberg W.M., Borshchev A. V., and Filippov A.E. NIDA Symposium on AIDS, Cancer and Related Problems, May 26, 2004, St. Petersburg, Russia

Mathematical modeling is a relatively new but fast developing area of HIV studies providing researchers with an additional dynamical dimension in epidemiological work that allows scientists to simulate the consequences of various intervention and prevention scenarios. We illustrate these concepts by presenting a model that describes Injecting Drug Users (IDU) networks, injecting behavior and HIV/HCV spread within the networks. This individual-based (also called agent-based) model is used to investigate the impact of the introduction of Integralcannula syringes (ICS) instead of commonly used Detachable Needle syringes (DNS). Laboratory experiments have shown that ICS retain approximately 1000 times less residual blood (<.001 ml vs. 1ml) following injection and rinsing than DNS thereby decreasing risk of HIV/NCV transmission by nearly 100 times after 2 rinses.
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Scalable Mathematical Models for Substance Use: From Social Networks to the Whole Populations Georgiy V. Bobashev, William A. Zule, Elizabeth D. Root, Wendee M. Wechsberg, Andrei V. Borshchev, and Alex E. Filippov. The College on Problems of Drug Dependence 66th Annual Meeting, June 12–17, 2004, San Juan, Puerto Rico

Mathematical modeling is a relatively new but fast developing area of substance use field providing researchers with additional dynamical dimension in epidemiological work and allowing scientists to simulate the consequences of various intervention and prevention scenarios. We illustrate these concepts by presenting two models. The first model describes Injecting Drug Users (IDU) networks, injecting behavior and HIV/HCV spread among the networks. The size, structure of the networks as well as frequency of injecting and HIV risks were obtained from published literature on urban IDU networks. This individual-based model was used to investigate the impact of introduction of Integral-cannula syringes (ICS) instead of commonly used Detachable Needle syringes (DNS).
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