Genetic algorithms (GA) is an optimization technique for searching very large spaces that models the role of the genetic material in living organisms. A small population of individual exemplars can eectively search a large space because they contain schemata, useful substructures that can be potentially combined to make tter individuals. Formal studies of competing schemata show that the best policy for replicating them is to increase them exponentially according to their relative tness. This turns out to be the policy used by genetic algorithms.

GANotes.pdf

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