Grammatical Evolution; Evolutionary Automatic Programming in an Arbitrary Language

Ryan, Conor & Michael O'Neill

ISBN 10: 1402074441 / ISBN 13: 9781402074448

Published by Springer, 2003

About this Item

Covers have extremely minor wear to corners and edges. Interior and exterior book else in as new condition. International shipping billed at cost. Photos upon request.; Genetic Programming, 4; 8vo 8" - 9" tall; 144 pages.

Seller Inventory # 93307

Bibliographic Details

• Title: Grammatical Evolution; Evolutionary Automatic Programming in an Arbitrary Language
• Publisher: Springer
• Publication Date: 2003
• Language: English
• ISBN 10: 1402074441
• ISBN 13: 9781402074448
• Binding: Hardcover
• Condition: Near Fine
• Seller catalogs:
  • Computers & Internet

About this title

Synopsis

Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language provides the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search. Grammatical Evolution's rich modularity gives a unique flexibility, making it possible to use alternative search strategies - whether evolutionary, deterministic or some other approach - and to even radically change its behavior by merely changing the grammar supplied. This approach to Genetic Programming represents a powerful new weapon in the Machine Learning toolkit that can be applied to a diverse set of problem domains.

Review

From the reviews:

"This is the first book written on grammatical evolution, a new technique that is receiving increasing attention and use. Therefore, the book fulfills an important role ... . The book contains a good description of grammatical evolution ... . ‘Grammatical Evolution’ should be useful for specialists and Ph.D. students in the field of grammatical evolution and genetic programming, and people working in artificial intelligence and genetic algorithms in general. We would advise it as a good resource for university libraries." (Manuel Alfonseca and Alfonso Ortega, Genetic programming and Evolvable Machines, Vol. 5, 2004)