by Eisuke Kita
Publisher: InTech 2011
Number of pages: 584
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. Apart from mathematical optimization problems, evolutionary algorithms have also been used as an experimental framework within biological evolution and natural selection in the field of artificial life.
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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 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.
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 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.