Foundations of Genetic Programming

1. Front Matter

   Pages I-XV

   PDF

2. Introduction

   • William B. Langdon, Riccardo Poli

   Pages 1-16

3. Fitness Landscapes

   • William B. Langdon, Riccardo Poli

   Pages 17-26

4. Program Component Schema Theories

   • William B. Langdon, Riccardo Poli

   Pages 27-47

5. Pessimistic GP Schema Theories

   • William B. Langdon, Riccardo Poli

   Pages 49-68

6. Exact GP Schema Theorems

   • William B. Langdon, Riccardo Poli

   Pages 69-95

7. Lessons from the GP Schema Theory

   • William B. Langdon, Riccardo Poli

   Pages 97-111

8. The Genetic Programming Search Space

   • William B. Langdon, Riccardo Poli

   Pages 113-132

9. The GP Search Space: Theoretical Analysis

   • William B. Langdon, Riccardo Poli

   Pages 133-150

10. Example I: The Artificial Ant

    • William B. Langdon, Riccardo Poli

    Pages 151-174

11. Example II: The Max Problem

    • William B. Langdon, Riccardo Poli

    Pages 175-192

12. GP Convergence and Bloat

    • William B. Langdon, Riccardo Poli

    Pages 193-217

13. Conclusions

    • William B. Langdon, Riccardo Poli

    Pages 219-221

14. Back Matter

    Pages 223-260

    PDF

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.

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

From the reviews:

I came to this book from an engineering perspective as a GP practitioner
interested in practical issues such as which cross-over operator was most
applicable for my problem. Whilst this book did not offer any clear-cut
answers, this is a reflection of the fact that there are no clear-cut answers,
yet. What the book does succeed in doing is providing an illuminating overview
of the body of work which will, in time, come to provide a theoretical
foundation, and accurate prescriptions, for all of the ad-hoc tweaks and
adjustments that we make in practise.
This was published in the British Computer Society journal "Expert Update", 5(3) p46, 2002 by Steve Phelps.

"Is genetic programming (GP) better than random search? … Langdon and Poli take on the ambitious task of giving a unified overview of a field still in its infancy, and the result is an invaluable companion to the literature. The book … proceeds to give a comprehensive and illuminating treatment of the most important theorems. … throughout the book the formal side of the theory is developed alongside intuitive explanations and constructive analysis of actual empirical data." (Steve Phelps, Expert Update, Vol. 5 (3), 2002)

"The book ‘Foundations of Genetics Programming’ summarizes appearances and approaches in the GP section. … There are many references for details in the text. Naturally, a large list of references is printed in the appendix. In conclusion, the book describes general principles of genetic programming. I recommend this as the first book for those who are familiarized with the GA and want to be in the know of the GP." (Vít Fábera, Neural Network World, Vol. 12 (4), 2002)

• Computer Science, University College, London, London, UK

  William B. Langdon

• Department of Computer Science, The University of Essex, Colchester, UK

  Riccardo Poli

Policies and ethics