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Computational Intelligence

Collaboration, Fusion and Emergence

  • Christine L. Mumford
  • Lakhmi C. Jain

Part of the Intelligent Systems Reference Library book series (ISRL, volume 1)

Table of contents

  1. Front Matter
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Christine L. Mumford
      Pages 3-21
  3. Fusing Evolutionary Algorithms and Fuzzy Logic

  4. Adaptive Solution Schemes

    1. Front Matter
      Pages 175-175
    2. Edmund K. Burke, Mathew R. Hyde, Graham Kendall, Gabriela Ochoa, Ender Ozcan, John R. Woodward
      Pages 177-201
    3. James E. Borrett, Edward P. K. Tsang
      Pages 203-230
  5. Multi-agent Systems

    1. Front Matter
      Pages 231-231
    2. Mahmoud Efatmaneshnik, Carl Reidsema
      Pages 275-320
    3. Mair Allen-Williams, Nicholas R. Jennings
      Pages 321-360
    4. Minjie Zhang, Quan Bai, Fenghui Ren, John Fulcher
      Pages 361-399
  6. Computer Vision

    1. Front Matter
      Pages 401-401
    2. Sheryl Brahnam, Loris Nanni
      Pages 403-439
    3. B. Zhan, P. Remagnino, D. N. Monekosso, S. Velastin
      Pages 441-472
  7. Communications for CI Systems

    1. Front Matter
      Pages 473-473
    2. Giorgio Biagetti, Paolo Crippa, Francesco Gianfelici, Claudio Turchetti
      Pages 475-500
    3. Bruno Apolloni, Guglielmo Apolloni, Simone Bassis, Gian Luca Galliani, Gianpaolo Rossi
      Pages 501-524
  8. Artificial Immune Systems

    1. Front Matter
      Pages 525-525
    2. Emma Hart, Chris McEwan, Despina Davoudani
      Pages 527-558
  9. Parallel Evolutionary Algorithms

    1. Front Matter
      Pages 559-559
  10. CI for Clustering and Classification

  11. Back Matter

About this book

Introduction

This book is the first in a new series entitled "Intelligent Systems Reference Library". It is a collection of chapters written by leading experts, covering a rich and diverse variety of computer-based techniques, all involving some aspect of computational intelligence (CI). Authors in this collection recognize the limitations of individual paradigms, and propose some practical and novel ways in which different CI techniques can be combined with each other, or with more traditional computational techniques, to produce powerful problem-solving environments.

Common themes to be found in the various chapters of this collection include the following:

  • Fusion,
  • Collaboration, and
  • Emergence.

Fusion describes the hybridization of two or more techniques, at least one of which will involve CI. Collaboration ensures that the different techniques work effectively together. Finally, Emergence refers to the phenomenon that complex behaviour can arise as a result of collaboration between simple processing elements.

The book covers a wide range of cutting edge techniques and applications, and is divided into the following parts:

I. Introduction

II. Fusing evolutionary algorithms and fuzzy logic

III. Adaptive solution schemes

IV. Multi-agent systems

V. Computer vision

VI. Communication for CI systems

VII. Artificial immune systems

VIII. Parallel evolutionary algorithms

IX. CI for clustering and classification

Keywords

Multi-agent system agents case-based reasoning computational intelligence evolution evolutionary algorithm evolutionary computation fuzzy logic fuzzy system genetic programming learning modeling

Editors and affiliations

  • Christine L. Mumford
    • 1
  • Lakhmi C. Jain
    • 2
  1. 1.School of Computer ScienceCardiff University CardiffUK
  2. 2.University of South Australia Adelaide South AustraliaAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-01799-5
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-01798-8
  • Online ISBN 978-3-642-01799-5
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site