改进HTN规划的顺序优化，减少冗余约束。
Lose the Order, Keep the Hierarchy: Deordering HTN Plans
- 将经典规划的去序技术扩展至层次任务网络约束。
- 在IPC 2023基准上显著减少计划中的排序约束数量。
- 适合关注计划简洁性与可执行性的自动化系统研究者。
层次任务网络（HTN）规划是一种基于任务分解的强大规划形式。尽管已有大量研究聚焦于计划生成，但对生成后优化的关注较少，尤其是计划去序问题——即在保持计划有效性的同时移除不必要的动作间顺序约束——在HTN领域仍研究不足。本文将经典规划中两种成熟的去序技术拓展至考虑层次分解约束的场景。我们在IPC 2023部分有序HTN基准上评估了所提方法，并与直接生成部分有序计划的Optiplan HTN规划器进行对比。结果表明，两种实现均显著减少了排序约束数量；虽然也观察到关键路径长度有所缩短，但改善程度较弱。
原文摘要 · Abstract (English)
Hierarchical Task Network (HTN) planning is a powerful planning formalism based on task decomposition. Although most of the literature studied plan generation, comparatively less attention has been paid to post-plan optimization. In particular, plan deordering has been extensively studied in classical planning but remains under-researched in the HTN setting. Plan deordering removes unnecessary ordering constraints between actions in a plan whilst keeping the plan valid. In this paper, we adapt two established plan deordering techniques from classical planning by extending the techniques to account for hierarchical decomposition constraints. We evaluate our proposed approaches on the IPC 2023 Partial-Order HTN benchmarks and we compare them against Optiplan, an HTN planner that generates partially ordered plans directly. Our results show a substantial reduction in number of ordering constraints in both our implementations. Although we also observe a reduction in critical path length, the improvements are less pronounced.
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