提出了一种称为可纳子目标排序(admissible subgoal ordering,简称ASO)的排序关系,给出了可纳排序的形式化定义并讨论其对增量式规划的重要性.随后介绍了原子依赖关系理论和原子依赖图技术,能够在多项式时间内近似求解可纳子目标排序关系.最后给出了一种计算可纳子目标序列的算法.其所有思想已经在规划系统ASOP中实现通过在国际规划大赛标准测试领域问题上的实验,其结果表明,该方法能够有效地求解大规模的规划问题,并能极大地改善规划性能.
This paper proposes an ordering relation named Admissible Subgoal Ordering (ASO). The definition of ASO is formalized, and its relative importance for incremental planning is discussed. Then, this paper introduces the notion of dependency relations over facts, and develops fact dependency graph technique that can approximate admissible ordering relations in polynomial time. Finally, an algorithm to compute subgoals sequence with admissible orderings is presented. All the ideas presented in the paper are implemented in the planning system ASOP, and the effectiveness of the techniques is demonstrated on the benchmarks of International Planning Competitions (IPC). The results show that these techniques can efficiently solve large planning problems and lead to a greater improvement in planning performance.