This paper presents SibylSat, a novel SAT-based method designed to efficiently solve totally-ordered HTN problems (TOHTN). In contrast to prevailing SAT-based HTN planners that employ a breadth-first search strategy, SibylSat adopts a greedy search approach, enabling it to identify promising decompositions for expansion. The selection process is facilitated by a heuristic derived from solving a relaxed problem, which is also expressed as a SAT problem. Our experimental evaluations demonstrate that SibylSat outperforms existing SAT-based TOHTN approaches in terms of both runtime and plan quality on most of the IPC benchmarks, while also solving a larger number of problems.

翻译：本文提出SibylSat，一种新颖的基于SAT的方法，旨在高效求解全序HTN问题（TOHTN）。与当前采用广度优先搜索策略的基于SAT的HTN规划器不同，SibylSat采用贪婪搜索方法，使其能够识别有前景的分解进行扩展。该选择过程通过求解一个松弛问题（同样表述为SAT问题）所导出的启发式信息来辅助实现。我们的实验评估表明，在大多数IPC基准测试中，SibylSat在运行时间和规划质量方面均优于现有的基于SAT的TOHTN方法，同时能够求解更多的问题。