A core challenge of evolutionary search is the need to balance between exploration of the search space and exploitation of highly fit regions. Quality-diversity search has explicitly walked this tightrope between a population's diversity and its quality. This paper extends a popular quality-diversity search algorithm, MAP-Elites, by treating the selection of parents as a multi-armed bandit problem. Using variations of the upper-confidence bound to select parents from under-explored but potentially rewarding areas of the search space can accelerate the discovery of new regions as well as improve its archive's total quality. The paper tests an indirect measure of quality for parent selection: the survival rate of a parent's offspring. Results show that maintaining a balance between exploration and exploitation leads to the most diverse and high-quality set of solutions in three different testbeds.

翻译：进化搜索的一个核心挑战是,必须在探索搜索空间与开发高度适中的区域之间取得平衡; 高质量多样性搜索在人口多样性及其质量之间明确走过这一紧身线; 本文扩展了大众的高质量搜索算法(MAP-Elites),将父母的选择视为多武装强盗问题; 利用从探索不足但可能有好处的搜索空间选择父母的上游信任度的变化,可以加快新区域的发现,并改善其档案的总体质量; 论文测试了选择父母的间接质量衡量标准:父母后代的生存率; 研究结果显示,在探索与开发之间保持平衡,可以在三个不同的测试中找到最多样化和最高质量的解决方案。