Genetic Algorithms and Heuristic Search

Terry Jones
Santa Fe Institute
1399 Hyde Park Road
Santa Fe, NM 87501, USA
terry@santafe.edu

and

Stephanie Forrest
Department of Computer Science
University of New Mexico
Albuquerque, NM 87131, USA
forrest@cs.unm.edu

Abstract

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 towards answering a question that has been the subject of much research in the GAs community: what makes search hard (or easy) for a GA?

Terry Jones (terry <AT> jon.es)