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 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.
by Sebastian Ventura (ed.) - InTech
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 ...
by Thomas Weise
The book on global optimization algorithms - methods to find optimal solutions for given problems. It focuses on evolutionary algorithms, genetic algorithms, genetic programming, learning classifier systems, evolution strategy, etc.