Abstract
The locality of the mapping from genotype to phenotype is an important issue in the study of landscapes and problem difficulty in evolutionary computation. In tree-structured Genetic Programming (GP), the locality approach is not generally applied because no explicit genotype-phenotype mapping exists, in contrast to some other GP encodings. In this paper we define GP phenotypes in terms of semantics or behaviour. For a given problem, a model of one or more phenotypes and mappings between them may be appropriate e.g. g ? p0, where g is the genotype, pi are distinct types of phenotypes, and f is fitness. Thus, the behaviour of each component mapping can be studied separately. The locality of the genotype-phenotype mapping can also be decomposed into the effects of the encoding and those of the operator’s genotypic step-size. Two standard benchmark problem classes–Boolean and artificial ant–are studied in a principled way using this fine-grained view of locality. The method of studying locality with phenotypes seems useful in the case of the artificial ant, but Boolean problems provide a counter-example.
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McDermott, J., Galván-Lopéz, E., O’Neill, M. (2011). A Fine-Grained View of Phenotypes and Locality in Genetic Programming. In: Riolo, R., Vladislavleva, E., Moore, J. (eds) Genetic Programming Theory and Practice IX. Genetic and Evolutionary Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1770-5_4
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