Document Type

Working Paper

Publication Date

2002

Subjects

Evolutionary computation -- Analysis, Evolutionary programming (Computer science)

Abstract

Previous work on coevolutionary search has demonstrated both successful and unsuccessful applications. As a step in explaining what factors lead to success or failure, we present a comparative study of an evolutionary and a coevolutionary search model. In the latter model, strategies for solving a problem coevolve with training cases. We find that the coevolutionary model has a relatively large efficacy: 86 out of 100 (86%) of the simulations produce high quality strategies. In contrast, the evolutionary model has a very low efficacy: a high quality strategy is found in only two out of 100 runs (2%). We show that the increased efficacy in the coevolutionary model results from the direct exploitation of low quality strategies by the population of training cases. We also present evidence that the generality of the high-quality strategies can suffer as a result of this same exploitation.

Description

Santa Fe Institute Working Paper: 2002-01-002.

©NOTICE: This working paper is included by permission of the contributing author(s) as a means to ensure timely distribution of the scholarly and technical work on a non-commercial basis. Copyright and all rights therein are maintained by the author(s). It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may be reposted only with the explicit permission of the copyright holder.

Subsequently published in the International Journal of Computational Intelligence and Applications, 02, 53 (2002). DOI: 10.1142/S1469026802000427

DOI

10.1142/S1469026802000427

Persistent Identifier

http://archives.pdx.edu/ds/psu/12302

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