Abstract
Size fair and homologous crossover genetic operators for tree based genetic programming are described and tested. Both produce considerably reduced increases in program size (i.e., less bloat) and no detrimental effect on GP performance.
GP search spaces are partitioned by the ridge in the number of program v. their size and depth. While search efficiency is little effected by initial conditions, these do strongly influence which half of the search space is searched. However a ramped uniform random initialization is described which straddles the ridge.
With subtree crossover trees increase about one level per generation leading to subquadratic bloat in program length.
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Langdon, W.B. Size Fair and Homologous Tree Crossovers for Tree Genetic Programming. Genetic Programming and Evolvable Machines 1, 95–119 (2000). https://doi.org/10.1023/A:1010024515191
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DOI: https://doi.org/10.1023/A:1010024515191