Co-evolutionary Probabilistic Structured Grammatical Evolution

TL;DR

This paper introduces Co-evolutionary Probabilistic Structured Grammatical Evolution (Co-PSGE), a novel method that co-evolves grammars and genotypes, outperforming existing grammatical evolution techniques on benchmark problems.

Contribution

It presents a new co-evolutionary framework that evolves both grammars and genotypes simultaneously, enhancing the performance of structured grammatical evolution.

Findings

Co-PSGE outperforms GE, PGE, and SGE on most benchmark problems.

The approach shows statistically significant improvements.

Co-PSGE effectively adapts grammars during evolution.

Abstract

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.