Evolution can be viewed as a particular class of search algorithms that involve the alternation of two steps, one expanding a population of solution candidates by generating new candidates according to some relatively simple stochastic rule (such as random mutation or sexual recombination), the other contracting the population by pruning candidates that score poorly when tested by an evaluation function.
