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Genetic algorithms are one of the more successful machine learning methods. Based on the metaphor of natural evolution, a genetic algorithm searches the available information in any given task and seeks the optimum solution by replacing weaker populations with stronger ones.
Includes research from academia, government laboratories, and industry
Contains high calibre papers which have been extensively reviewed
Continues the tradition of presenting not only current theoretical work but also issues that could shape future research in the field
Ideal for researchers in machine learning, specifically those involved with evolutionary computation

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