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  • Conference proceedings
  • © 2003

Adaptive Agents and Multi-Agent Systems

Adaptation and Multi-Agent Learning

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2636)

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 2001. AAMAS 2002.

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Table of contents (18 papers)

  1. Front Matter

    Pages I-XIV
  2. Learning, Co-operation, and Communication

    1. Cooperative Multiagent Learning

      • Enric Plaza, Santiago Ontañón
      Pages 1-17
    2. Reinforcement Learning Approaches to Coordination in Cooperative Multi-agent Systems

      • Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens
      Pages 18-32
    3. Cooperative Learning Using Advice Exchange

      • Luís Nunes, Eugénio Oliveira
      Pages 33-48
    4. Environmental Risk, Cooperation, and Communication Complexity

      • Peter Andras, Gilbert Roberts, John Lazarus
      Pages 49-65
    5. Multiagent Learning for Open Systems: A Study in Opponent Classification

      • Michael Rovatsos, Gerhard Weiß, Marco Wolf
      Pages 66-87
  3. Emergence and Evolution in Multi-agent Systems

    1. Adapting Populations of Agents

      • Philippe De Wilde, Maria Chli, L. Correia, R. Ribeiro, P. Mariano, V. Abramov et al.
      Pages 110-124
    2. Evolving Preferences among Emergent Groups of Agents

      • Paul Marrow, Cefn Hoile, Fang Wang, Erwin Bonsma
      Pages 159-173
    3. Structuring Agents for Adaptation

      • Sander van Splunter, Niek J. E. Wijngaards, Frances M. T. Brazier
      Pages 174-186
    4. Stochastic Simulation of Inherited Kinship-Driven Altruism

      • Heather Turner, Dimitar Kazakov
      Pages 187-201
  4. Theoretical Foundations of Adaptive Agents

    1. Using Cognition and Learning to Improve Agents’ Reactions

      • Pedro Rafael Graça, Graça Gaspar
      Pages 239-259
    2. TTree: Tree-Based State Generalization with Temporally Abstract Actions

      • William T. B. Uther, Manuela M. Veloso
      Pages 260-290
    3. Using Landscape Theory to Measure Learning Difficulty for Adaptive Agents

      • Christopher H. Brooks, Edmund H. Durfee
      Pages 291-305
  5. Back Matter

    Pages 323-323

Other Volumes

  1. Adaptive Agents and Multi-Agent Systems

About this book

Adaptive Agents and Multi-Agent Systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, computer science, software engineering, and developmental biology, as well as cognitive and social science.

This book surveys the state of the art in this emerging field by drawing together thoroughly selected reviewed papers from two related workshops; as well as papers by leading researchers specifically solicited for this book. The articles are organized into topical sections on

- learning, cooperation, and communication

- emergence and evolution in multi-agent systems

- theoretical foundations of adaptive agents

Editors and Affiliations

  • Department of Computing, City University, London, UK

    Eduardo Alonso

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

    Daniel Kudenko, Dimitar Kazakov

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access