Grammatical evolution (GE) is one of the most widespread techniques in evolutionary computation. Genotypes in GE are bit strings while phenotypes are strings, of a language defined by a user-provided context-free grammar. In this paper, we propose a novel procedure for mapping genotypes to phenotypes that we call weighted hierarchical GE (WHGE). WHGE imposes a form of hierarchy on the genotype and encodes grammar symbols with a varying number of bits based on the relative expressive power of those symbols. WHGE does not impose any constraint on the overall GE framework, in particular, WHGE may handle recursive grammars, uses the classical genetic operators, and does not need to define any bound in advance on the size of phenotypes. We assessed experimentally our proposal in depth on a set of challenging and carefully selected benchmarks, comparing the results of the standard GE framework as well as two of the most significant enhancements proposed in the literature: 1) position-independent GE and 2) structured GE. Our results show that WHGE delivers very good results in terms of fitness as well as in terms of the properties of the genotype-phenotype mapping procedure.

中文翻译：

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加权层次语法演化


语法进化（GE）是进化计算中最广泛使用的技术之一。 GE 中的基因型是位字符串，而表型是由用户提供的上下文无关语法定义的语言的字符串。在本文中，我们提出了一种将基因型映射到表型的新程序，我们称之为加权分层 GE (WHGE)。 WHGE 对基因型强加了一种层次结构，并根据这些符号的相对表达能力用不同的位数对语法符号进行编码。 WHGE不会对整个GE框架施加任何约束，特别是WHGE可以处理递归语法，使用经典的遗传算子，并且不需要预先定义表型大小的任何界限。我们在一组具有挑战性且精心挑选的基准上对我们的提案进行了深入的实验评估，比较了标准 GE 框架的结果以及文献中提出的两个最重要的增强功能：1）位置无关的 GE 和 2）结构化 GE 。我们的结果表明，WHGE 在适合度以及基因型-表型作图程序的特性方面提供了非常好的结果。