Co-evolutionary Probabilistic Structured Grammatical Evolution

被引:4
作者
Megane, Jessica [1 ]
Lourenco, Nuno [1 ]
Machado, Penousal [1 ]
机构
[1] Univ Coimbra, Coimbra, Portugal
来源
PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'22) | 2022年
关键词
probabilistic algorithms; grammar-based; Gaussian mutation; co-evolution;
D O I
10.1145/3512290.3528833
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:991 / 999
页数:9
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