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Foundations of Genetic Programming

  • William B. Langdon
  • Riccardo Poli

Table of contents

  1. Front Matter
    Pages I-XV
  2. William B. Langdon, Riccardo Poli
    Pages 1-16
  3. William B. Langdon, Riccardo Poli
    Pages 17-26
  4. William B. Langdon, Riccardo Poli
    Pages 27-47
  5. William B. Langdon, Riccardo Poli
    Pages 49-68
  6. William B. Langdon, Riccardo Poli
    Pages 69-95
  7. William B. Langdon, Riccardo Poli
    Pages 97-111
  8. William B. Langdon, Riccardo Poli
    Pages 113-132
  9. William B. Langdon, Riccardo Poli
    Pages 133-150
  10. William B. Langdon, Riccardo Poli
    Pages 151-174
  11. William B. Langdon, Riccardo Poli
    Pages 175-192
  12. William B. Langdon, Riccardo Poli
    Pages 193-217
  13. William B. Langdon, Riccardo Poli
    Pages 219-221
  14. Back Matter
    Pages 223-260

About this book

Introduction

Genetic programming (GP), one of the most advanced forms of evolutionary computation, has been highly successful as a technique for getting computers to automatically solve problems without having to tell them explicitly how. Since its inceptions more than ten years ago, GP has been used to solve practical problems in a variety of application fields. Along with this ad-hoc engineering approaches interest increased in how and why GP works. This book provides a coherent consolidation of recent work on the theoretical foundations of GP. A concise introduction to GP and genetic algorithms (GA) is followed by a discussion of fitness landscapes and other theoretical approaches to natural and artificial evolution. Having surveyed early approaches to GP theory it presents new exact schema analysis, showing that it applies to GP as well as to the simpler GAs. New results on the potentially infinite number of possible programs are followed by two chapters applying these new techniques.

Keywords

Artificial Intelligence Automatic Programming Computer Computer Science Evolutionary Computation Genetic Programming Problem Solving Search Algorithms Symbol algorithms calculus genetic algorithms programming

Authors and affiliations

  • William B. Langdon
    • 1
  • Riccardo Poli
    • 2
  1. 1.Computer ScienceUniversity College, LondonLondonUK
  2. 2.Department of Computer ScienceThe University of EssexColchesterUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-04726-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-07632-9
  • Online ISBN 978-3-662-04726-2
  • Buy this book on publisher's site