探索的探索：测量词汇选择找到最优模糊路径的能力
An Exploration of Exploration: Measuring the ability of lexicase selection to find obscure pathways to optimality
摘要：
父选择算法（选择方案）引导种群通过问题的搜索空间，通常在开发和探索之间进行权衡。理解选择方案如何影响搜索空间内的开发和探索对于解决日益具有挑战性的问题至关重要。在这里，我们介绍了一个“探索诊断”，诊断选择方案的能力，搜索空间探索。我们使用我们的探索诊断调查的词汇选择和它的几个变种的探索能力：双词汇，下采样词汇，队列词汇，和新奇词汇。我们验证，词库选择探索比赛选择，我们表明，词库选择的探索能力可以是敏感的人口规模和用于评估候选解决方案的测试用例的数量之间的比率。此外，我们发现，放松词典的精英主义与词典可以进一步提高探索。下采样和队列lexicase -两种技术应用随机抽样测试案例-降低lexicase的探索能力，但是，我们发现，队列分区更好地保留lexicase的探索能力比下采样。最后，我们发现证据表明，新奇词典的新奇测试用例的增加，可以降低词典的探索能力。总的来说，我们的研究结果提供了进一步探索和可操作的见解和建议，使用词库选择的假设。此外，这项工作证明了价值的选择方案诊断作为一种补充，更传统的基准方法选择方案分析。
英文摘要：
Parent selection algorithms (selection schemes) steer populations through a problem's search space, often trading off between exploitation and exploration. Understanding how selection schemes affect exploitation and exploration within a search space is crucial to tackling increasingly challenging problems. Here, we introduce an "exploration diagnostic" that diagnoses a selection scheme's capacity for search space exploration. We use our exploration diagnostic to investigate the exploratory capacity of lexicase selection and several of its variants: epsilon lexicase, down-sampled lexicase, cohort lexicase, and novelty-lexicase. We verify that lexicase selection out-explores tournament selection, and we show that lexicase selection's exploratory capacity can be sensitive to the ratio between population size and the number of test cases used for evaluating candidate solutions. Additionally, we find that relaxing lexicase's elitism with epsilon lexicase can further improve exploration. Both down-sampling and cohort lexicase -- two techniques for applying random subsampling to test cases -- degrade lexicase's exploratory capacity; however, we find that cohort partitioning better preserves lexicase's exploratory capacity than down-sampling. Finally, we find evidence that novelty-lexicase's addition of novelty test cases can degrade lexicase's capacity for exploration. Overall, our findings provide hypotheses for further exploration and actionable insights and recommendations for using lexicase selection. Additionally, this work demonstrates the value of selection scheme diagnostics as a complement to more conventional benchmarking approaches to selection scheme analysis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
