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Knowledge Incorporation in Evolutionary Computation

  • Yaochu Jin

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 167)

Table of contents

  1. Front Matter
    Pages I-XIII
  2. Introduction

    1. Front Matter
      Pages 1-1
  3. Knowledge Incorporation in Initialization, Recombination and Mutation

    1. Front Matter
      Pages 13-13
    2. Keith Bearpark, Andy J. Keane
      Pages 15-36
    3. Ricardo Landa Becerra, Carlos A. Coello Coello
      Pages 37-55
    4. David A. Ostrowski, Robert G. Reynolds
      Pages 81-102
    5. Jun Zhang, Henry S. H. Chung, Alan W. L. Lo, B. J. Hu
      Pages 123-143
  4. Knowledge Incorporation in Selection and Reproduction

    1. Front Matter
      Pages 145-145
    2. Peter A. N. Bosman, Dirk Thierens
      Pages 147-176
    3. Els I. Ducheyne, B. De Baets, R. De Wulf
      Pages 177-194
    4. Pei-Chann Chang, Jih-Chang Hsieh, Yen-Wen Wang
      Pages 215-236
    5. Federico Divina, Elena Marchiori
      Pages 237-253
  5. Knowledge Incorporation in Fitness Evaluations

    1. Front Matter
      Pages 279-279
    2. Yaochu Jin, Michael Hüsken, Markus Olhofer, Bernhard Sendhoff
      Pages 281-306
    3. Holger Ulmer, Felix Streichert, Andreas Zell
      Pages 333-355
  6. Knowledge Incorporation through Life-time Learning and Human-Computer Interactions

    1. Front Matter
      Pages 357-357
    2. Kim W. C. Ku, M. W. Mak
      Pages 359-383
    3. Tadahiko Murata, Shiori Kaige, Hisao Ishibuchi
      Pages 385-410
    4. Ian C. Parmee, Johnson A. Abraham
      Pages 435-458
  7. Preference Incorporation in Multi-objective Evolutionary Computation

    1. Front Matter
      Pages 459-459
    2. Dragan Cvetković, Carlos A. Coello Coello
      Pages 479-502
    3. Jiachuan Wang, Janis P. Terpenny
      Pages 525-543
  8. Back Matter
    Pages 545-548

About this book

Introduction

This carefully edited book puts together the state-of-the-art and recent advances in knowledge incorporation in evolutionary computation within a unified framework. The book provides a comprehensive self-contained view of knowledge incorporation in evolutionary computation including a concise introduction to evolutionary algorithms as well as knowledge representation methods. "Knowledge Incorporation in Evolutionary Computation" is a valuable reference for researchers, students and professionals from engineering and computer science, in particular in the areas of artificial intelligence, soft computing, natural computing, and evolutionary computation.

Keywords

Case-Based Reasoning Computer Evolution Strategies Evolutionary Computation Fuzzy Fuzzy Systems Genetic Algorithms Genetic programming Knowledge Incorporation Knowledge Representations human-computer interaction intelligence knowledge representation optimization programming

Editors and affiliations

  • Yaochu Jin
    • 1
  1. 1.Honda Research Institute Europe GmbHOffenbach/MainGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-44511-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2005
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-06174-5
  • Online ISBN 978-3-540-44511-1
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site