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Quantitative Analysis of Locally Geometric Semantic Crossover
Krzysztof Krawiec and Tomasz Pawlak
Institute of Computing Science, Poznan University of Technology, Pozna
, Poland
kkrawiec@cs.put.poznan.pl
tpawlak@cs.put.poznan.pl
Abstract. We investigate the properties of locally geometric semantic crossover (LGX), a genetic programming search operator that is approximately semantically geometric on the level of homologous code fragments. For a pair of corresponding loci in the parents, LGX finds a semantically intermediate procedure from a library prepared prior to evolutionary run, and creates an offspring by using such procedure as replacement code. LGX proves superior when compared to standard subtree crossover and other control methods in terms of search convergence, test-set performance, and time required to find a high-quality solution. This paper focuses in particular the impact of homology and program semantic on LGX performance.
Keywords: genetic programming, semantic crossover, homology
LNCS 7491, p. 397 ff.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2012