Multi-Agent and Multi-Agent-Based Simulation

1. Front Matter

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2. Simulation of Multi-agent Systems

   1. Smooth Scaling Ahead: Progressive MAS Simulation from Single PCs to Grids

      • Les Gasser, Kelvin Kakugawa, Brant Chee, Marc Esteva

      Pages 1-10

   2. Agent Communication in Distributed Simulations

      • Fang Wang, Stephen John Turner, Lihua Wang

      Pages 11-24

   3. Distributed Simulation of MAS

      • Michael Lees, Brian Logan, Rob Minson, Ton Oguara, Georgios Theodoropoulos

      Pages 25-36

   4. Extending Time Management Support for Multi-agent Systems

      • Alexander Helleboogh, Tom Holvoet, Danny Weyns, Yolande Berbers

      Pages 37-48

   5. Designing and Implementing MABS in AKIRA

      • Giovanni Pezzulo, Gianguglielmo Calvi

      Pages 49-64

3. Technique and Technology

   1. Work-Environment Analysis: Environment Centric Multi-agent Simulation for Design of Socio-technical Systems

      • Anuj P. Shah, Amy R. Pritchett

      Pages 65-77

   2. Layering Social Interaction Scenarios on Environmental Simulation

      • Daisuke Torii, Toru Ishida, Stéphane Bonneaud, Alexis Drogoul

      Pages 78-88

   3. Change Your Tags Fast! – A Necessary Condition for Cooperation?

      • David Hales

      Pages 89-98

   4. Users Matter: A Multi-agent Systems Model of High Performance Computing Cluster Users

      • Michael J. North, Cynthia S. Hood

      Pages 99-113

   5. Formal Analysis of Meeting Protocols

      • Catholijn M. Jonker, Martijn Schut, Jan Treur, Pınar Yolum

      Pages 114-129

4. Methodology and Modelling

   1. From KISS to KIDS – An ‘Anti-simplistic’ Modelling Approach

      • Bruce Edmonds, Scott Moss

      Pages 130-144

   2. Analysis of Learning Types in an Artificial Market

      • Kiyoshi Izumi, Tomohisa Yamashita, Koichi Kurumatani

      Pages 145-158

   3. Toward Guidelines for Modeling Learning Agents in Multiagent-Based Simulation: Implications from Q-Learning and Sarsa Agents

      • Keiki Takadama, Hironori Fujita

      Pages 159-172

5. Social Dynamics

   1. Agent-Based Modelling of Forces in Crowds

      • Colin M. Henein, Tony White

      Pages 173-184

   2. An Investigation into the Use of Group Dynamics for Solving Social Dilemmas

      • Tomohisa Yamashita, Kiyoshi Izumi, Koichi Kurumatani

      Pages 185-194

6. Applications

   1. ASAP: Agent-Based Simulator for Amusement Park

      • Kazuo Miyashita

      Pages 195-209

   2. Patchiness and Prosociality: An Agent-Based Model of Plio/Pleistocene Hominid Food Sharing

      • L. S. Premo

      Pages 210-224

   3. Plant Disease Incursion Management

      • Lisa Elliston, Ray Hinde, Alasebu Yainshet

      Pages 225-235

   4. A Hybrid Micro-Simulator for Determining the Effects of Governmental Control Policies on Transport Chains

      • Markus Bergkvist, Paul Davidsson, Jan A. Persson, Linda Ramstedt

      Pages 236-247

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.

• Performance
• SAP
• Simulation
• agent societies
• agent-based model
• agent-based simulation
• agent-based systems
• communication
• distributed simulation
• learning
• multi-agent simulation
• multi-agent system
• multi-agent systems
• multiagent systems
• social modeling

• 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

Policies and ethics