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Evolutionary Computing

AISB Workshop, Leeds, U.K., April 11 - 13, 1994. Selected Papers

  • Conference proceedings
  • © 1994

Overview

Editors:
  1. Terence C. Fogarty
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 865)

Included in the following conference series:

Conference proceedings info: AISB EC 1994.

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Table of contents (24 papers)

  1. Front Matter

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  2. Formal memetic algorithms

    • Nicholas J. Radcliffe, Patrick D. Surry
    Pages 1-16

  3. A statistical mechanical formulation of the dynamics of genetic algorithms

    • Jonathan Shapiro, Adam Prügel-Bennett, Magnus Rattray
    Pages 17-27

  4. Evolutionary stability in simple classifier systems

    • D. F. Yates, A. Fairley
    Pages 28-37

  5. Nonbinary transforms for genetic algorithm problems

    • Paul Field
    Pages 38-50

  6. Enhancing evolutionary computation using analogues of biological mechanisms

    • Ray Paton
    Pages 51-64

  7. Exploiting mate choice in evolutionary computation: Sexual selection as a process of search, optimization, and diversification

    • Geoffrey F. Miller
    Pages 65-79

  8. An empirical comparison of selection methods in evolutionary algorithms

    • Peter J. B. Hancock
    Pages 80-94

  9. An evolution strategy and genetic algorithm hybrid: An initial implementation and first results

    • Lawrence Bull, Terence C Fogarty
    Pages 95-102

  10. Genetic algorithms and directed adaptation

    • John Coyne, Ray Paton
    Pages 103-114

  11. Genetic algorithms and neighbourhood search

    • Colin R. Reeves
    Pages 115-130

  12. A unified paradigm for parallel Genetic Algorithms

    • A. Kapsalis, G. D. Smith, V. J. Rayward-Smith
    Pages 131-149

  13. Distributed coevolutionary genetic algorithms for multi-criteria and multi-constraint optimisation

    • Phil Husbands
    Pages 150-165

  14. Inductive operators and rule repair in a hybrid genetic learning system: Some initial results

    • A. Fairley, D. F. Yates
    Pages 166-179

  15. Adaptive learning of a robot arm

    • Mukesh J. Patel, Marco Dorigo
    Pages 180-194

  16. Co-evolving Co-operative populations of rules in learning control systems

    • Terence C. Fogarty
    Pages 195-209

  17. Learning anticipatory behaviour using a delayed action classifier system

    • Brian Carse
    Pages 210-223

  18. Applying a restricted mating policy to determine state space niches using immediate and delayed reinforcement

    • Chris Melhuish, Terence C. Fogarty
    Pages 224-237

  19. A comparison between two architectures for searching and learning in maze problems

    • A. G. Pipe, B. Carse
    Pages 238-249

  20. Fast practical evolutionary timetabling

    • Dave Corne, Peter Ross, Hsiao-Lan Fang
    Pages 250-263
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  1. Evolutionary Computing

Keywords

About this book

This volume is based on the Workshop on Evolutionary Computing held in Leeds, U.K. in April 1994 under the sponsorship of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. In addition to the 22 best papers presented at the workshop, there are two invited contributions by Ray Paton and Colin Reever.
The volume addresses several aspects of evolutionary computing, particularly genetic algorithms, and its applications, for example in search, robotics, signal processing, machine learning, and scheduling. The papers are organized in sections on theoretical and biological foundations, techniques, classifier systems, and applications.

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