Stephanie Forrest, Terry Jones

Paper #: 95-02-021

Genetic Algorithms (GAs) and heuristic search are shown to be structurally similar. The strength of the correspondence and its practical consequences are demonstrated by considering the relationship between fitness functions in GAs and the heuristic functions of AI. By examining the extent to which fitness functions approximate an AI ideal, a measure of GA search difficulty is defined and applied to previously studied problems. The success of the measure in predicting GA performance (1) illustrates the potential advantages of viewing evolutionary search from a heuristic search perspective and (2) appears to be an important step toward answering a question that has been the subject of much research in the GAs community: what makes search hard (or easy) for a GA?