Methodological Guidelines for Modeling and Developing MAS-Based Simulations

The intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch.

Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. This comprehensive resource reviews two decades of research in the intersection of MAS, simulation, and different application domains. It provides scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field's history and its basic principles, as well as cataloging the various simulation engines for MAS, the book devotes three sections to current and emerging approaches and applications.

Simulation for MAS - explains simulation support for agent decision making, the use of simulation for the design of self-organizing systems, the role of software architecture in simulating MAS, and the use of simulation for studying learning and stigmergic interaction.

MAS for Simulation - discusses an agent-based framework for symbiotic simulation, the use of country databases and expert systems for agent-based modeling of social systems, crowd-behavior modeling, agent-based modeling and simulation of adult stem cells, and agents for traffic simulation.

Tools - presents a number of representative platforms and tools for MAS and simulation, including Jason, James II, SeSAm, and RoboCup Rescue.

Complete with over 200 figures and formulas, this reference book provides the necessary overview of experiences with MAS simulation and the tools needed to exploit simulation in MAS for future research in a vast array of applications including home security, computational systems biology, and traffic management.

Over the past two decades, the field of multi-agent systems has been applied for designing modeling and simulation problems and, conversely, simulation has often been used for the design of multi-agent systems in a variety of applications domains. The objective of this book, edited by Uhrmacher (Institute of Computer Science, U. of Rostock, Germany) and Weyns (Ph.D., computer science, Katholieke U. Leuven, Belgium), is to provide a comprehensive overview of the research at the intersection of multi-agent systems, simulation, and application domains, covering such aspects as modeling abstractions, methodological approaches, formal foundations, and platforms in different domains. The material is presented in four parts, with the first providing an overview of the intersection and co-evolution of the two fields from the perspectives of the agent community and social science; the second discussing the use of simulation in multi-agent systems; the third examining the use of multi-agent systems for simulation; and the last presenting a number of state-of-the-art platforms and tools for multi-agent systems and simulations. Annotation ©2009 Book News, Inc., Portland, OR (booknews.com)

Multiple agent systems(MAS) have been used extensively as a tool for designing simulation problems; while simulation has often been used for the design of multiple agent studies. This book focuses on the intersection of MAS and simulation, emphasizing application domains. The book starts with a historical overview from different perspectives. A second part discusses the use of simulation in MAS and among a wealth of topics, explains simulation support for agent decision making. A third section zooms in on MAS for simulation and a last section presents a number of representative platforms and tools for MAS and simulation.

This comprehensive reference provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. It reviews two decades of research in the intersection of MAS, simulation, and different application domains to provide scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field's history and basic principles it catalogs the various simulation engines for MAS. Complete with over 200 figures and formulas, the text devotes three sections to current and emerging approaches and applications.