Co-evolutionary Probabilistic Structured Grammatical Evolution
Published in Genetic and Evolutionary Computation Conference (GECCO), 2022
Jessica Mégane, Nuno Lourenço, and Penousal Machado
This work proposes an extension to Structured Grammatical Evolution (SGE) called Co-evolutionary Probabilistic Structured Grammatical Evolution (Co-PSGE). In Co-PSGE each individual in the population is composed by a grammar and a genotype, which is a list of dynamic lists, each corresponding to a non-terminal of the grammar containing real numbers that correspond to the probability of choosing a derivation rule. Each individual uses its own grammar to map the genotype into a program. During the evolutionary process, both the grammar and the genotype are subject to variation operators.
The performance of the proposed approach is compared to 3 different methods, namely, Grammatical Evolution (GE), Probabilistic Grammatical Evolution (PGE), and SGE on four different benchmark problems. The results show the effectiveness of the approach since Co-PSGE is able to outperform all the methods with statistically significant differences in the majority of the problems.
Jessica Mégane, Nuno Lourenço, and Penousal Machado. 2022. Co-evolutionary probabilistic structured grammatical evolution. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘22). Association for Computing Machinery, New York, NY, USA, 991–999. https://doi.org/10.1145/3512290.3528833