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  • Conference proceedings
  • © 2005

Adaptive Agents and Multi-Agent Systems II

Adaptation and Multi-Agent Learning

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3394)

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

Conference series link(s): AAMAS: European Symposium on Adaptive Agents and Multi-Agent Systems

Conference proceedings info: AAMAS 2004. AAMAS 2003.

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  • ISBN: 978-3-540-32274-0
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Table of contents (19 papers)

  1. Front Matter

  2. Postext – A Mind for Society

    • Avishalom Shalit, Tom Erez, Anna Deters, Uri Hershberg, Eran Shir, Sorin Solomon
    Pages 24-40
  3. Towards Time Management Adaptability in Multi-agent Systems

    • Alexander Helleboogh, Tom Holvoet, Danny Weyns, Yolande Berbers
    Pages 88-105
  4. Learning to Coordinate Using Commitment Sequences in Cooperative Multi-agent Systems

    • Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens
    Pages 106-118
  5. Evolving the Game of Life

    • Dimitar Kazakov, Matthew Sweet
    Pages 132-146
  6. Dynamic and Distributed Interaction Protocols

    • Jarred McGinnis, David Robertson
    Pages 167-184
  7. Experiments in Subsymbolic Action Planning with Mobile Robots

    • John Pisokas, Ulrich Nehmzow
    Pages 216-229
  8. Robust Online Reputation Mechanism by Stochastic Approximation

    • Takamichi Sakai, Kenji Terada, Tadashi Araragi
    Pages 230-244
  9. Learning Multi-agent Search Strategies

    • Malcolm J. A. Strens
    Pages 245-259
  10. Multi-agent Reinforcement Learning in Stochastic Single and Multi-stage Games

    • Katja Verbeeck, Ann Nowé, Maarten Peeters, Karl Tuyls
    Pages 275-294
  11. Towards Adaptive Role Selection for Behavior-Based Agents

    • Danny Weyns, Kurt Schelfthout, Tom Holvoet, Olivier Glorieux
    Pages 295-312

Other Volumes

  1. Adaptive Agents and Multi-Agent Systems II

    Adaptation and Multi-Agent Learning

About this book

Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science.

This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.

Keywords

  • agents
  • artificial intelligence
  • autonomous agent
  • evolution
  • intelligence
  • learning
  • machine learning
  • multi-agent system

Editors and Affiliations

  • Department of Computer Science, University of York, York, UK

    Daniel Kudenko

  • Artificial Intelligence Group, Department of Computer Science, University of York, Heslington, York, UK

    Dimitar Kazakov

  • Department of Computing, City University, London, United Kingdom

    Eduardo Alonso

Bibliographic Information

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • ISBN: 978-3-540-32274-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 109.00
Price excludes VAT (USA)