带边选择器的路径最短路径问题的统一形式
A Unifying Formalism for Shortest Path Problems with Expensive Edge Evaluations via Lazy Best-First Search over Paths with Edge Selectors
摘要：
虽然最短路径问题有无数的应用，合适的算法的计算效率密切依赖于底层的问题域。在本文中，我们专注于域评估边缘权重函数占主导地位的算法运行时间。在机器人运动规划的方法的启发，我们定义和调查的懒惰最短路径类的算法，区分边缘选择器功能的选择。我们表明，在文献中的几个算法是等效的，这个懒惰的算法适当选择这个选择器。此外，我们提出了各种新的选择器的灵感来自采样和统计力学，并发现这些选择器优于现有的算法上的一组示例问题。
英文摘要：
While the shortest path problem has myriad applications, the computational efficiency of suitable algorithms depends intimately on the underlying problem domain. In this paper, we focus on domains where evaluating the edge weight function dominates algorithm running time. Inspired by approaches in robotic motion planning, we define and investigate the Lazy Shortest Path class of algorithms which is differentiated by the choice of an edge selector function. We show that several algorithms in the literature are equivalent to this lazy algorithm for appropriate choice of this selector. Further, we propose various novel selectors inspired by sampling and statistical mechanics, and find that these selectors outperform existing algorithms on a set of example problems.
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。
