In most genetic programming systems, candidate solution programs themselves serve as the genetic material 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 can have detrimental effects on evolutionary search. In prior work, structured programs were linearised prior to variation in order to facilitate uniformity, but this necessitated syntactic repair after variation, which reintroduced non-uniformities. In this chapter we describe a new approach that uses linear genomes, from which structured programs are expressed only for the purpose of fitness testing. We present the new approach in detail and show how it facilitates both uniform variation and the evolution of programs with meaningful structure.
CITATION STYLE
Helmuth, T., Spector, L., McPhee, N. F., & Shanabrook, S. (2018). Linear Genomes for Structured Programs (pp. 85–100). https://doi.org/10.1007/978-3-319-97088-2_6
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