Abstract
The loss of genetic diversity in evolutionary algorithms may lead to suboptimal solutions. Many techniques have been developed for maintaining diversity in genetic algorithms, but few investigations have been done for genetic programs. We define here a diversity measure for genetic programs based on our metric for genetic trees [3]. We use this distance measure for studying the effects of fitness sharing. We then propose a method for adaptively maintaining the diversity of a population during evolution.
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Ekárt, A., Németh, S.Z. (2002). Maintaining the Diversity of Genetic Programs. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A. (eds) Genetic Programming. EuroGP 2002. Lecture Notes in Computer Science, vol 2278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45984-7_16
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DOI: https://doi.org/10.1007/3-540-45984-7_16
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