Abstract
In most genetic programming systems, candidate solution programs themselves serve as genome upon which variation operators act. However, because of the hierarchical structure of computer programs and the syntactic constraints that they must obey, it is difficult to implement variation operators that affect different parts of programs with uniform probability. This lack of uniformity can have detrimental effects on evolutionary search, such as increases in code bloat. In prior work, structured programs were linearized prior to variation in order to facilitate uniform variation. However, this necessitated syntactic repair after variation, which reintroduced non-uniformities. In this chapter we describe a new approach that uses linear genomes that are translated into hierarchical programs for execution. We present the new approach in detail and show how it facilitates both uniform variation and the evolution of programs with meaningful structure.
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Linear Push.
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This material is based upon work supported by the National Science Foundation under Grants No. 1129139 and 1331283. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Helmuth, T., Spector, L., McPhee, N.F., Shanabrook, S. (2018). Linear Genomes for Structured Programs. In: Riolo, R., Worzel, B., Goldman, B., Tozier, B. (eds) Genetic Programming Theory and Practice XIV. Genetic and Evolutionary Computation. Springer, Cham. https://doi.org/10.1007/978-3-319-97088-2_6
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