Advertisement

Adaptive Agents and Multi-Agent Systems

Adaptation and Multi-Agent Learning

  • Eduardo Alonso
  • Daniel Kudenko
  • Dimitar Kazakov
Conference proceedings AAMAS 2002, AAMAS 2001

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

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 2636)

Table of contents

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

    1. Enric Plaza, Santiago Ontañón
      Pages 1-17
    2. Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens
      Pages 18-32
    3. Luís Nunes, Eugénio Oliveira
      Pages 33-48
    4. Peter Andras, Gilbert Roberts, John Lazarus
      Pages 49-65
    5. Michael Rovatsos, Gerhard Weiß, Marco Wolf
      Pages 66-87
  3. Emergence and Evolution in Multi-agent Systems

    1. Philippe De Wilde, Maria Chli, L. Correia, R. Ribeiro, P. Mariano, V. Abramov et al.
      Pages 110-124
    2. Paul Marrow, Cefn Hoile, Fang Wang, Erwin Bonsma
      Pages 159-173
    3. Sander van Splunter, Niek J. E. Wijngaards, Frances M. T. Brazier
      Pages 174-186
    4. Heather Turner, Dimitar Kazakov
      Pages 187-201
  4. Theoretical Foundations of Adaptive Agents

  5. Back Matter
    Pages 323-323

About these proceedings

Introduction

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

Keywords

MAS Multi-agent system adaptation adaptive agents adaptive learning adaptive systems agent-based simulation agent-based systems agents artificial intelligence evolution intelligence learning machine learning multi-agent systems

Editors and affiliations

  • Eduardo Alonso
    • 1
  • Daniel Kudenko
    • 2
  • Dimitar Kazakov
    • 2
  1. 1.Department of ComputingCity UniversityLondonUK
  2. 2.Department of Computer ScienceUniversity of YorkHeslington, YorkUK

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-44826-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 2003
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-40068-4
  • Online ISBN 978-3-540-44826-6
  • Series Print ISSN 0302-9743
  • Buy this book on publisher's site