Foundations of Genetic Programming
| Author | : | |
| Rating | : | 4.50 (522 Votes) |
| Asin | : | 3540424512 |
| Format Type | : | paperback |
| Number of Pages | : | 260 Pages |
| Publish Date | : | 2014-09-19 |
| Language | : | English |
DESCRIPTION:
Whilst this book did not offer any clear-cutanswers, this is a reflection of the fact that there are no clear-cut answers,yet. The book … proceeds to give a comprehensive and illuminating treatment of the most important theorems. … There are many references for details in the text. 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. From the reviews:I came to this book from an engineering perspective as a GP practitionerinterested in practical issues such
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 very useful metaphor of what you'll be attempting to do, as a researcher. However, the authors carefully point out the limitations of this idea. Notably that some spaces might have no natural metric.The book th. "Exciting New Developments in EC Theory" according to Chris Stephens. 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.. dean_from_sa said A survey of what was new in "A survey of what was new in 2002" according to dean_from_sa. 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 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. C. - 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. C. 00"A survey of what was new in 2002" according to dean_from_sa. 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 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. C. - 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. C. . This book was published in "A survey of what was new in 2002" according to dean_from_sa. 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 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. C. - 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. C. 00"A survey of what was new in 2002" according to dean_from_sa. 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 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. C. - 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. C. 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 "A survey of what was new in 2002" according to dean_from_sa. 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 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. C. - 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. C. discusses the problems with the fitness landscape. Chapter 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. C. - 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. C
This is one of the only books to provide a complete and coherent review of the theory of genetic programming (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. In doing so, it provides a coherent consolidation of recent work on the theoretical foundations of GP. 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.