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Multi-Agent and Multi-Agent-Based Simulation

Joint Workshop MABS 2004

  • Conference proceedings
  • © 2005

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3415)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: MABS 2004.

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Table of contents (20 papers)

  1. Simulation of Multi-agent Systems

  2. Technique and Technology

  3. Methodology and Modelling

  4. Social Dynamics

  5. Applications

Other volumes

  1. Multi-Agent and Multi-Agent-Based Simulation

Keywords

About this book

This volume presents revised and extended versions of selected papers presented at the Joint Workshop on Multi-Agent and Multi-Agent-Based Simulation, a workshop federated with the 3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), which was held in New York City, USA, July 19–23, 2004. The workshop was in part a continuation of the International Workshop on Multi-Agent-Based Simulation (MABS) series. - vised versions of papers presented at the four previous MABS workshops have been published as volumes 1534, 1979, 2581, and 2927 in the Lecture Notes in Arti?cial Intelligence series. The aim of the workshop was to provide a forum for work in both appli- tions of multi-agent-based simulation and the technical challenges of simulating large multi-agent systems (MAS). There has been considerable recent progress in modelling and analyzing multi-agent systems, and in techniques that apply MAS models to complex real-world systems such as social systems and organi- tions. Simulation is an increasingly important strand that weaves together this work. In high-risk, high-cost situations, simulations provide critical cost/bene?t leverage, and make possible explorations that cannot be carried out in situ: – Multi-agentapproachestosimulatingcomplexsystemsarekeytoolsinint- disciplinary studies of social systems. Agent-based social simulation (ABSS) researchsimulatesandsynthesizessocialbehaviorinordertounderstandreal social systems with properties of self-organization, scalability, robustness, and openness. – IntheMAScommunity,simulationhasbeenappliedtoawiderangeofMAS research and design problems, from models of complex individual agents - ploying sophisticated internal mechanisms to models of large-scale societies of relativelysimple agents which focus more on the interactions between agents.

Editors and Affiliations

  • Department of Systems and Software Engineering, School of Engineering, Blekinge Institute of Technology, Ronneby, Sweden

    Paul Davidsson

  • School of Computer Science, University of Nottingham, Nottingham, UK

    Brian Logan

  • Tokyo Institute of Technology, tokyo, Japan

    Keiki Takadama

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