Grammatical Evolution

Evolutionary Automatic Programming in an Arbitrary Language

  • Michael O’Neill
  • Conor Ryan

Part of the Genetic Programming Series book series (GPEM, volume 4)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Michael O’Neil, Conor Ryan
    Pages 1-4
  3. Michael O’Neil, Conor Ryan
    Pages 5-21
  4. Michael O’Neil, Conor Ryan
    Pages 23-32
  5. Michael O’Neil, Conor Ryan
    Pages 33-47
  6. Michael O’Neil, Conor Ryan
    Pages 49-62
  7. Michael O’Neil, Conor Ryan
    Pages 63-77
  8. Michael O’Neil, Conor Ryan
    Pages 79-98
  9. Michael O’Neil, Conor Ryan
    Pages 99-128
  10. Michael O’Neil, Conor Ryan
    Pages 129-132
  11. Back Matter
    Pages 133-144

About this book

Introduction

Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language provides the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search. Grammatical Evolution's rich modularity gives a unique flexibility, making it possible to use alternative search strategies - whether evolutionary, deterministic or some other approach - and to even radically change its behavior by merely changing the grammar supplied. This approach to Genetic Programming represents a powerful new weapon in the Machine Learning toolkit that can be applied to a diverse set of problem domains.

Keywords

Extension algorithms behavior code evolution genetic algorithms genetic programming grammar grammars learning logic logic programming machine learning programming search strategy

Authors and affiliations

  • Michael O’Neill
    • 1
  • Conor Ryan
    • 1
  1. 1.University of LimerickIreland

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-0447-4
  • Copyright Information Kluwer Academic Publishers 2003
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5081-1
  • Online ISBN 978-1-4615-0447-4
  • Series Print ISSN 1566-7863
  • About this book