evolutionary programming

evolutionary programming [‚ev·ə¦lü·shə‚ner·ē ′prō‚gram·iŋ]

(computer science)

Computer programming with genetic algorithms. Also known as evolutionary computation; genetic programming.

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evolutionary programming - (EP) A stochastic optimisation strategy originally conceived by Lawrence J. Fogel in 1960. An initially random population of individuals (trial solutions) is created. Mutations are then applied to each individual to create new individuals. Mutations vary in the severity of their effect on the behaviour of the individual. The new individuals are then compared in a "tournament" to select which should survive to form the new population. EP is similar to a genetic algorithm, but models only the behavioural linkage between parents and their offspring, rather than seeking to emulate specific genetic operators from nature such as the encoding of behaviour in a genome and recombination by genetic crossover. EP is also similar to an evolution strategy (ES) although the two approaches developed independently. In EP, selection is by comparison with a randomly chosen set of other individuals whereas ES typically uses deterministic selection in which the worst individuals are purged from the population.