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Learning and Adaption in Multi-Agent Systems

First International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers

  • Conference proceedings
  • © 2006

Overview

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3898)

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

Included in the following conference series:

Conference proceedings info: LAMAS 2005.

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Table of contents (13 papers)

Other volumes

  1. Learning and Adaption in Multi-Agent Systems

Keywords

About this book

This book contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?rst results.

Editors and Affiliations

  • MICC-IKAT, Universiteit Maastricht, The Netherlands

    Karl Tuyls

  • Center for Mathematics and Computer Science (CWI), Amsterdam, The Netherlands

    Pieter Jan’t Hoen

  • KaHo Sint-Lieven, Information Technology Group, Gent, Belgium

    Katja Verbeeck

  • Department of Mathematical and Computer Science, University of Tulsa, USA

    Sandip Sen

Bibliographic Information

  • Book Title: Learning and Adaption in Multi-Agent Systems

  • Book Subtitle: First International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers

  • Editors: Karl Tuyls, Pieter Jan’t Hoen, Katja Verbeeck, Sandip Sen

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/11691839

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2006

  • Softcover ISBN: 978-3-540-33053-0Published: 10 April 2006

  • eBook ISBN: 978-3-540-33059-2Published: 07 March 2006

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 217

  • Topics: Artificial Intelligence, Computer Communication Networks

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