Genotype-to-phenotype mappings translate genotypic variations such as mutations into phenotypic changes. Neutrality is the observation that some mutations do not lead to phenotypic changes. Studying the search trajectories in genotypic and phenotypic spaces, especially through neutral mutations, helps us to better understand the progression of evolution and its algorithmic behaviour. In this study, we visualise the search trajectories of a genetic programming system as graph-based models, where nodes are genotypes/phenotypes and edges represent their mutational transitions. We also quantitatively measure the characteristics of phenotypes including their genotypic abundance (the requirement for neutrality) and Kolmogorov complexity. We connect these quantified metrics with search trajectory visualisations, and find that more complex phenotypes are under-represented by fewer genotypes and are harder for evolution to discover. Less complex phenotypes, on the other hand, are over-represented by genotypes, are easier to find, and frequently serve as stepping-stones for evolution.
翻译:Genotype-to-phenopytype 映射将基因编程系统的搜索轨迹转换成基于图形的模型,其中节点是基因型/人型,边缘代表其突变转变。我们也从数量上测量了人型类型的特点,包括它们的基因型丰度(中立要求)和科尔莫戈洛夫复杂程度。我们将这些量化指标与搜索轨迹的视觉化联系起来,并发现更复杂的人型类型被较少的基因型代表不足,而且更难进化。在另一方面,较复杂的人型被基因型代表过大,并且常常成为进化的垫石。