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Real-Time Search for Learning Autonomous Agents

  • Toru Ishida

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Norifumi Mizuno
    Pages 1-16
  3. Masashi Shimbo
    Pages 17-34
  4. Richard Korf
    Pages 35-65
  5. Back Matter
    Pages 119-126

About this book

Introduction

Autonomous agents or multiagent systems are computational systems in which several computational agents interact or work together to perform some set of tasks. These systems may involve computational agents having common goals or distinct goals.
Real-Time Search for Learning Autonomous Agents focuses on extending real-time search algorithms for autonomous agents and for a multiagent world. Although real-time search provides an attractive framework for resource-bounded problem solving, the behavior of the problem solver is not rational enough for autonomous agents. The problem solver always keeps the record of its moves and the problem solver cannot utilize and improve previous experiments. Other problems are that although the algorithms interleave planning and execution, they cannot be directly applied to a multiagent world. The problem solver cannot adapt to the dynamically changing goals and the problem solver cannot cooperatively solve problems with other problem solvers. This book deals with all these issues.
Real-Time Search for Learning Autonomous Agents serves as an excellent resource for researchers and engineers interested in both practical references and some theoretical basis for agent/multiagent systems. The book can also be used as a text for advanced courses on the subject.

Keywords

agents algorithms autonom autonomous agents behavior control controlling learning organization performance problem solving search algorithm

Authors and affiliations

  • Toru Ishida
    • 1
  1. 1.Kyoto UniversityJapan

Bibliographic information

  • DOI https://doi.org/10.1007/b102407
  • Copyright Information Kluwer Academic Publishers 1997
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-7923-9944-5
  • Online ISBN 978-0-585-34507-9
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site
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