Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP

Authors:
Darrell Whitley;Marc Richards;Ross Beveridge;Andre' da Motta Salles Barreto
Affiliations:
Colorado State University Fort Collins, CO;Colorado State University Fort Collins, CO;Colorado State University Fort Collins, CO;Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
Venue:
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Year:
2006

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Abstract

In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over time as to which replacement strategies and selection methods are best. The question addressed in this paper is relatively simple: since there are so many variants of evolutionary algorithm, how well do some of the other well known forms of evolutionary algorithm perform when used to evolve programs trees using s-expressions as the representation? Our results suggest a wide range of evolutionary algorithms are all equally good at evolving programs, including the simplest evolution strategies.