Product Description

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

• Amazon Sales Rank: #206247 in Books
• Published on: 2002-03-22
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 260 pages

Review

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)

Customer Reviews

Exciting New Developments in EC Theory
Langdon and Poli are both internationally recognized experts in Evolutionary Computation (EC) and, in particular, Genetic Programming. They have both contributed extensively to the theoretical "foundations" of GP and hence may speak with no small degree of authority about GP theory. As a physicist working in EC I like the balance that the authors have struck between mathematical rigor and understandable intuition. The book is not as rigorous as Vose's well known GA book. However, it is much easier to read. Neither does it take the "engineering" rule of thumb approach, as does Goldberg's book for instance. It covers very well recent important developments in the theory of GP and in that sense makes very good reading for anyone with a serious interest in EC theory. It is not for the novice, even though technically it is not a difficult book. It is really a research monograph and not a textbook. In that sense the title is a little bit misplaced. With the exciting direction the authors are pointing in I believe that in five years time another book of the same title should truly be able to lay out what are the foundations of GP theory and also show the theoretical unity that exists between the different branches of EC.

A survey of what was new in 2002
This book was published in 2002 to provide a survey of the direction research had taken in the field of Genetic Programming. There is an explanation of what genetic programming is and how it is different from genetic algorithms in chapter 1(GP is a "generalization" of GA). Chapter 2 discusses the problems with the fitness landscape. Chapter 3 - 6 discusses various schema theory approaches and proofs. Chapter 6 has a great explanation of effective fitness.

There are numerous theorems and proofs in the book. There are informative examples of the max problem and the artificial ant (Santa Fe Trail) problems. Chapter 11 is about how GP convergences are a tricky matter and how subtrees can hide interesting incidences of convergence.

This is not an introductory text, it is intended for graduate level or higher readers. There is much theoretical work here and a limited background in this area will result in limited understanding of the material.

Good introduction to GP theory
Langdon and Poli do a fantastic job of summarizing the major theoretical results of genetic programming. The first chapter gives a quick and clear introduction to genetic programming. They continue with a comprehensive summary of previous research in schema theory, and then they present their exciting theoretical results. Their description of an exact schema theorem (microscopic and macroscopic) for GP is a bit dense, but they provide a good discussion of how to interpret these results. As a whole, this book is generally easy to follow, even with little prior exposure to genetic programming. Of course, this book is not intended to be a general introduction to genetic programming (one of John Koza's books would be more appropriate), but instead it is intended to present some of the theoretical foundations of the field.