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Genetic Algorithms

Models that optimize rules by mimicking the Darwinian notion of survival of the fittest. A set of rules is chosen from those that work the best. The weakest are discarded. In addition, two successful rules can be combined (the equivalent to genetic cross-overs) to produce offspring rules. The offspring can replace the parents, or they will be discarded if less successful than the parents. Mutation is also accomplished by randomly changing elements. Mutation and cross-over occur with low probability, as in nature.

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