Abstract
In many genetic programming systems, the program variation and execution processes operate on different program representations. The representations on which variation operates are referred to as genomes. Unconstrained linear genome representations can provide a variety of advantages, including reduced complexity of program generation, variation, simplification and serialization operations. The Plush genome representation, which uses epigenetic markers on linear genomes to express nonlinear structures, has supported the production of state-of-the-art results in program synthesis with the PushGP genetic programming system. Here we present a new, simpler, non-epigenetic alternative to Plush, called Plushy, that appears to maintain all of the advantages of Plush while providing additional benefits. These results illustrate the virtues of unconstrained linear genome representations more generally, and may be transferable to genetic programming systems that target different languages for evolved programs.
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Acknowledgements
Feedback and discussions that improved this work were provided by other members of the Hampshire College Institute for Computational Intelligence, and by participants in the Genetic Programming Theory and Practice workshop.
This material is based upon work supported by the National Science Foundation under Grant No. 1617087. 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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Pantridge, E., Helmuth, T., Spector, L. (2020). Comparison of Linear Genome Representations for Software Synthesis. In: Banzhaf, W., Goodman, E., Sheneman, L., Trujillo, L., Worzel, B. (eds) Genetic Programming Theory and Practice XVII. Genetic and Evolutionary Computation. Springer, Cham. https://doi.org/10.1007/978-3-030-39958-0_13
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