GRT规划系统：前向状态空间规划中的后向启发式构造
The GRT Planning System: Backward Heuristic Construction in Forward State-Space Planning
摘要：
本文介绍了GRT，一个独立于领域的启发式规划系统的CNOPS世界。GRT分两个阶段解决问题。在预处理阶段，它向后估计每个事实与问题目标之间的距离。然后，在搜索阶段，使用这些估计来进一步估计每个中间状态与目标之间的距离，从而在向前方向上并且在最佳优先的基础上引导搜索过程。本文介绍了从预处理和搜索阶段之间采用相反的方向的好处，讨论了在预处理阶段出现的一些困难，并介绍了技术，以应付他们。此外，它提出了几种方法来提高启发式的效率，丰富的表示和减少问题的大小。最后，提出了一种基于域公理的克服局部最优状态的方法。该方法将复杂问题分解为一个个较简单的子问题，依次求解。从各个领域的性能结果，包括最近的规划比赛，表明GRT是最快的规划者之一。
英文摘要：
This paper presents GRT, a domain-independent heuristic planning system for STRIPS worlds. GRT solves problems in two phases. In the pre-processing phase, it estimates the distance between each fact and the goals of the problem, in a backward direction. Then, in the search phase, these estimates are used in order to further estimate the distance between each intermediate state and the goals, guiding so the search process in a forward direction and on a best-first basis. The paper presents the benefits from the adoption of opposite directions between the preprocessing and the search phases, discusses some difficulties that arise in the pre-processing phase and introduces techniques to cope with them. Moreover, it presents several methods of improving the efficiency of the heuristic, by enriching the representation and by reducing the size of the problem. Finally, a method of overcoming local optimal states, based on domain axioms, is proposed. According to it, difficult problems are decomposed into easier sub-problems that have to be solved sequentially. The performance results from various domains, including those of the recent planning competitions, show that GRT is among the fastest planners.
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。
