Genetic Programming: New Approaches and Successful Applications
by Sebastian Ventura (ed.)
Publisher: InTech 2012
Number of pages: 284
Genetic programming (GP) is a branch of Evolutionary Computing that aims the automatic discovery of programs to solve a given problem. Since its appearance, in the earliest nineties, GP has become one of the most promising paradigms for solving problems in the artificial intelligence field, producing a number of human-competitive results and even patentable new inventions.
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by R. Poli, W. B. Langdon, N. F. McPhee - Lulu.com
This book is an introduction to genetic programming GP is a systematic method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. GP has generated lots of results and applications.
by Adam Marczyk - The TalkOrigins Archive
Creationists argue that evolutionary processes cannot create new information, or that evolution has no practical benefits. This article disproves those claims by describing the explosive growth and widespread applications of genetic algorithms.
by L. Spector, W.B. Langdon, U. O'Reilly, P.J. Angeline - The MIT Press
Genetic programming is a form of evolutionary computation that evolves programs and program-like executable structures for developing reliable applications. This volume highlights the recent technical advances in this increasingly popular field.
by Witold Kosinski - InTech
With the recent trends towards massive data sets and significant computational power, evolutionary computation is becoming much more relevant to practice. The book presents recent improvements, ideas and concepts in a part of a huge EA field.