Assessment of problem modality by differential performance of lexicase selection in genetic programming: a preliminary report
Assessment of problem modality by differential performance of lexicase selection in genetic programming: a preliminary report
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通过遗传编程中词汇选择的差异性能评估问题模态：初步报告
DOI：
10.1145/2330784.2330846
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发表时间：
2012
影响因子：
3.9
通讯作者：
L. Spector
中科院分区：
文献类型：
--
作者：
L. Spector
遗传规划的许多潜在目标问题都是模态的，这意味着来自问题域不同区域的输入需要不同的响应模式。本文提出了一种用遗传规划解决模态问题的新方法，使用一种简单而新颖的亲本选择方法，称为词法选择。然后，它展示了遗传编程在有词法酶选择和没有词法酶选择的情况下的差异性能如何可以用来提供问题模态的度量，并且它认为，以这种方式定义这样的度量并不像最初出现的那样在方法上存在问题。通过对一个简单的模态符号回归问题的遗传规划运行分析，说明了模态测度。这是一份初步报告，部分目的是激发对模态问题的重要性、解决这些问题的方法以及测量问题模态的方法的讨论。虽然本文的核心概念是在遗传规划的背景下提出的，但它们也与其他形式的进化计算在模态问题中的应用有关。
Many potential target problems for genetic programming are modal in the sense that qualitatively different modes of response are required for inputs from different regions of the problem's domain. This paper presents a new approach to solving modal problems with genetic programming, using a simple and novel parent selection method called lexicase selection. It then shows how the differential performance of genetic programming with and without lexicase selection can be used to provide a measure of problem modality, and it argues that defining such a measure in this way is not as methodologically problematic as it may initially appear. The modality measure is illustrated through the analysis of genetic programming runs on a simple modal symbolic regression problem. This is a preliminary report that is intended in part to stimulate discussion on the significance of modal problems, methods for solving them, and methods for measuring the modality of problems. Although the core concepts in this paper are presented in the context of genetic programming, they are also relevant to applications of other forms of evolutionary computation to modal problems.