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 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 Moshe Sipper - Lulu.com
Moshe Sipper and his group have produced a plethora of award-winning results, in numerous games of diverse natures, evidencing the efficiency of evolutionary algorithms in general at producing top-notch, human-competitive game strategies.
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Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on.