Towards an understanding of locality in genetic programming
Towards an understanding of locality in genetic programming
复制标题
理解遗传编程中的局部性
DOI：
10.1145/1830483.1830646
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
A. Brabazon
中科院分区：
文献类型：
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作者：
E. López;James McDermott;M. O’Neill;A. Brabazon
局部性——邻近基因型与邻近表型的对应程度——已被定义为影响进化计算系统如何探索和利用搜索空间的关键因素。使用典型的遗传算法（GA）表示（即位串）对局部性进行了实证研究，并认为局部性在EC性能中起着重要作用。据我们所知，使用典型的遗传规划（GP）表示（即树状结构）进行局部性的明确研究很少。本文的目的是解决这一重要的研究差距。通过研究基因型与适合度的关系，将基因型-表型的定义扩展到GP。我们考虑将基于突变的GP系统应用于GP难以解决的两个问题（多模态欺骗性景观和高度中性景观）。为了详细分析这些情况下的局域性，我们采用了三种流行的变异算子。我们分析运营商的基因型步长在三个距离措施采取了专门的文献，并在相应的适应度值方面。我们还分析了不同大小的适应度变化的频率。
Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been defined as a key element affecting how Evolutionary Computation systems explore and exploit the search space. Locality has been studied empirically using the typical Genetic Algorithm (GA) representation (i.e., bitstrings), and it has been argued that locality plays an important role in EC performance. To our knowledge, there are few explicit studies of locality using the typical Genetic Programming (GP) representation (i.e., tree-like structures). The aim of this paper is to address this important research gap. We extend the genotype-phenotype definition of locality to GP by studying the relationship between genotypes and fitness. We consider a mutation-based GP system applied to two problems which are highly difficult to solve by GP (a multimodal deceptive landscape and a highly neutral landscape). To analyse in detail the locality in these instances, we adopt three popular mutation operators. We analyse the operators' genotypic step sizes in terms of three distance measures taken from the specialised literature and in terms of corresponding fitness values. We also analyse the frequencies of different sizes of fitness change.
DOI：
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发表时间：
1992
期刊：
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影响因子：
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作者：
J. Koza
通讯作者：
J. Koza