Description: 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 e ectively
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.
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GANotes.pdf
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