Motivation

• motivated by analogy to biological evolution
• GAs generate successor hypotheses by repeatedly mutating and recombining parts of the best currently known hypotheses
• a collection of hypotheses, population, is updated by replacing some fraction of the population by offspring of the most fit current hypotheses
• generate-and-test beam-search of hypotheses in which variants of the best current hypothesis are most likely to be considered next