Schema processing under proportional selection in the presence of random effects
David B. Fogel, Adam Ghozeil · IEEE Transactions on Evolutionary Computation · 1997
Traditional selection in genetic algorithms has relied on reproduction in proportion to observed fitness. This method of selection devotes samples to the observed schemata in a form described by the well known schema theorem. When schema fitness takes the form of a random variable, however, the expected number of samples from extant schemata may not be described by the schema theorem and varies according to the specific random variables involved.