Evolved to Win
by Moshe Sipper
Publisher: Lulu.com 2011
Number of pages: 193
Moshe Sipper and his group have produced a plethora of award-winning results, in numerous games of diverse natures, evidencing the success and efficiency of evolutionary algorithms in general -- and genetic programming in particular -- at producing top-notch, human-competitive game strategies. From classic chess and checkers, through simulated car racing and virtual warfare, to mind-bending puzzles, this book serves both as a tour de force of the research landscape and as a guide to the application of evolutionary computation within the domain of games.
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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.
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 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 Eisuke Kita - InTech
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.