Foundations of Genetic Programming / Edition 1

Foundations of Genetic Programming / Edition 1

by William B. Langdon, Riccardo Poli
ISBN-10:
3642076327
ISBN-13:
9783642076329
Pub. Date:
12/01/2010
Publisher:
Springer Berlin Heidelberg
ISBN-10:
3642076327
ISBN-13:
9783642076329
Pub. Date:
12/01/2010
Publisher:
Springer Berlin Heidelberg
Foundations of Genetic Programming / Edition 1

Foundations of Genetic Programming / Edition 1

by William B. Langdon, Riccardo Poli
$109.99
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Overview

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.

Product Details

ISBN-13: 9783642076329
Publisher: Springer Berlin Heidelberg
Publication date: 12/01/2010
Edition description: Softcover reprint of hardcover 1st ed. 2002
Pages: 260
Product dimensions: 6.10(w) x 9.25(h) x 0.24(d)

Table of Contents

1 Introduction.- 2 Fitness Landscapes.- 3 Program Component Schema Theories.- 4 Pessimistic GP Schema Theories.- 5 Exact GP Schema Theorems.- 6 Lessons from the GP Schema Theory.- 7 The Genetic Programming Search Space.- The GP Search Space: Theoretical Analysis.- 9 Example I: The Artificial Ant.- 10 Example II: The Max Problem.- 11 GP Convergence and Bloat.- 12 Conclusions.- A Genetic Programming Resources.- List of Special Symbols.
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