Engineering Intelligent Hybrid Multi-Agent Systems

  • Rajiv Khosla
  • Tharam Dillon

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Rajiv Khosla, Tharam Dillon
    Pages 1-18
  3. Rajiv Khosla, Tharam Dillon
    Pages 19-58
  4. Rajiv Khosla, Tharam Dillon
    Pages 59-104
  5. Rajiv Khosla, Tharam Dillon
    Pages 105-142
  6. Rajiv Khosla, Tharam Dillon
    Pages 143-177
  7. Rajiv Khosla, Tharam Dillon
    Pages 269-286
  8. Rajiv Khosla, Tharam Dillon
    Pages 287-309
  9. Rajiv Khosla, Tharam Dillon
    Pages 311-339
  10. Rajiv Khosla, Tharam Dillon
    Pages 341-365
  11. Rajiv Khosla, Tharam Dillon
    Pages 367-387
  12. Rajiv Khosla, Tharam Dillon
    Pages 389-395
  13. Back Matter
    Pages 397-410

About this book

Introduction

Engineering Intelligent Hybrid Multi-Agent Systems is about building intelligent hybrid systems. Included is coverage of applications and design concepts related to fusion systems, transformation systems and combination systems. These applications are in areas involving hybrid configurations of knowledge-based systems, case-based reasoning, fuzzy systems, artificial neural networks, genetic algorithms, and in knowledge discovery and data mining. Through examples and applications a synergy of these subjects is demonstrated.
The authors introduce a multi-agent architectural theory for engineering intelligent associative hybrid systems. The architectural theory is described at both the task structure level and the computational level. This problem-solving architecture is relevant for developing knowledge agents and information agents.
An enterprise-wide system modeling framework is outlined to facilitate forward and backward integration of systems developed in the knowledge, information, and data engineering layers of an organization. In the modeling process, software engineering aspects like agent oriented analysis, design and reuse are developed and described.
Engineering Intelligent Hybrid Multi-Agent Systems is the first book in the field to provide details of a multi-agent architecture for building intelligent hybrid systems.

Keywords

algorithms case-based reasoning data mining design fuzzy genetic algorithms knowledge knowledge discovery knowledge-based system knowledge-based systems modeling multi-agent system multi-agent systems neural networks system modeling

Authors and affiliations

  • Rajiv Khosla
    • 1
  • Tharam Dillon
    • 1
  1. 1.La Trobe UniversityMelbourneAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-6223-8
  • Copyright Information Kluwer Academic Publishers 1997
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7854-9
  • Online ISBN 978-1-4615-6223-8
  • About this book