Geometric Crossover in Syntactic Space
This paper presents a geometric crossover operator for Tree-Based Genetic Programming that acts on the syntactic space, where each expression tree is represented in prefix notation. The proposed operator is compared to the standard subtree crossover on a symbolic regression problem, on the Santa Fe Ant Trail and on a classification problem. Statistically validated results show that the individuals produced using this method are significantly smaller than those produced by the subtree crossover, and have similar or better performance in the target tasks.
KeywordsGenetic Programming Geometric operators Crossover
This article is based upon work from COST Action CA15140: Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO), supported by COST (European Cooperation in Science and Technology), www.cost.eu. Support by national funds through the Portuguese Foundation for Science and Technology (FCT) and by the European Regional Development Fund (FEDER) through COMPETE 2020 – Operational Program for Competitiveness and Internationalization (POCI) is also acknowledged. J. Macedo acknowledges the Portuguese Foundation for Science and Technology for Ph.D. studentship SFRH/BD/129673/2017.
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