Foundations of Genetic Programming
| Author | : | |
| Rating | : | 4.75 (692 Votes) |
| Asin | : | 3540424512 |
| Format Type | : | paperback |
| Number of Pages | : | 260 Pages |
| Publish Date | : | 2014-04-22 |
| Language | : | English |
DESCRIPTION:
W Boudville said specialised maths treatment of GP. This book can be usefully read along with a companion text by the same publisher - "Introduction to Evolutionary Computing". Langdon and Poli provide a focused look, on the specifics of genetic programming. The maths treatment here is significantly more involved than the other book.Foundations starts with what I suppose in this field is an obligatory section on the concept of a fitness landscape. A v. 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 understanda. 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.
… 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. … There are many references for details in the text. The book … proceeds to give a comprehensive and illuminating treatment of the most important theorems. 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. Whilst this book did not offer any clear-cutanswers, this is a reflection of the fact that there are no clear-cut answ
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.. In doing so, it provides a coherent consolidation of recent work on the theoretical foundations of GP. This is one of the only books to provide a complete and coherent review of the theory of genetic programming (GP)