William B. Langdon, Riccardo Poli

Foundations of Genetic Programming

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-642-07632-9
• Softcover reprint of hardcover 1st ed. 2002
• Seitenzahl: 276
• Erscheinungstermin: 30. November 2010
• Englisch
• Abmessung: 235mm x 155mm x 16mm
• Gewicht: 429g
• ISBN-13: 9783642076329
• ISBN-10: 3642076327
• Artikelnr.: 32055474

Autorenporträt

Genetic programming, 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 to solve them. Genetic Programming applications include financial modelling, electronic design, simulation, optimization, control, etc.

Inhaltsangabe

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.

Rezensionen

From the reviews: I came to this book from an engineering perspective as a GP practitionerinterested in practical issues such as which cross-over operator was mostapplicable for my problem. Whilst this book did not offer any clear-cutanswers, 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 overviewof the body of work which will, in time, come to provide a theoreticalfoundation, and accurate prescriptions, for all of the ad-hoc tweaks andadjustments 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)