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.
翻译：这项工作建议扩展称为 " 结构学进化(SGE) " 的结构学进化(SGE),称为 " 共同进化概率结构学进化(Co-PSGE) " 。在共同进化(PSGE)中,人口中的每一个人都由一个语法和基因型组成,这是一个动态列表,每组对应一个非语法的语法进化(SGE),包含与选择推导规则的概率相对应的真实数字。每个人使用自己的语法将基因型映射成一个程序。在进化过程中,语法和基因型都受到变量操作者的影响。拟议方法的性能与三种不同方法进行了比较,即:语法进化(GE)、概率学进化(PGEGE)和精度学进化(SGE),四个不同的基准问题。结果显示该方法的有效性,因为共同进化(PGEGE)能够超越所有方法,在大多数问题中具有统计上显著差异的方法。
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