Balancing parent and offspring selection in Genetic Programming

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Abstract

In order to drive Genetic Programming (GP) search towards an optimal situation, balancing selection pressure between the parent and offspring selection phases is an important aspect and very challenging. Our previous work showed that stochastic elements cannot be removed from both parent and offspring selections and suggested that maximising diversity in parents and minimising randomness in offspring could provide significantly good performance. This paper conducts additional carefully designed experiments to further investigate how diverse the parent should be if the offspring selection pressure is intensive. This paper shows that any attempt on adding more selection pressure to the parent selection can result in lower GP performance, and the higher the parent selection pressure, the worse the GP performance. The results confirm and strengthen the finding in our previous work. © Springer-Verlag Berlin Heidelberg 2009.

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APA

Xie, H., & Zhang, M. (2009). Balancing parent and offspring selection in Genetic Programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5866 LNAI, pp. 454–464). https://doi.org/10.1007/978-3-642-10439-8_46

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