Co-evolutionary Probabilistic Structured Grammatical Evolution

• Published in: arXiv.org
• Main Authors: Mégane, Jessica, Lourenço, Nuno, Machado, Penousal
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 19.04.2022
• Subjects: Computer Science - Neural and Evolutionary Computing; Evolution; Genotype & phenotype; Grammar; Real numbers; Statistical analysis; Statistical methods
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.2204.08985

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.