标题： 使用块替换提高计划执行的灵活性 显示英文标题

标题： Improving Plan Execution Flexibility using Block-Substitution

摘要： 部分顺序计划在人工智能规划中由于其较少的约束特性，促进了执行的灵活性。 最大化计划灵活性通过计划解序和计划重序的概念进行了研究。 计划解序移除了计划中的不必要的动作顺序，而计划重序则任意地修改它们以最小化动作顺序。 本研究与传统的计划解序和重序策略不同，通过将规划问题的子计划替换为计划外的动作来提高计划的灵活性。 我们利用块解序，通过在POP中封装连贯的动作来消除顺序，以构建动作块作为替换的候选子计划。 此外，本文引入了一种剪枝技术，用于消除BDPO计划中的冗余动作。 我们还评估了在结合基于MaxSAT的重序时的方法。 我们的实验结果表明，在国际规划竞赛（IPC）的基准问题上，计划执行的灵活性有了显著提高，同时保持了良好的覆盖率和执行时间。 显示英文摘要

摘要： Partial-order plans in AI planning facilitate execution flexibility due to their less-constrained nature. Maximizing plan flexibility has been studied through the notions of plan deordering, and plan reordering. Plan deordering removes unnecessary action orderings within a plan, while plan reordering modifies them arbitrarily to minimize action orderings. This study, in contrast with traditional plan deordering and reordering strategies, improves a plan's flexibility by substituting its subplans with actions outside the plan for a planning problem. We exploit block deordering, which eliminates orderings in a POP by encapsulating coherent actions in blocks, to construct action blocks as candidate subplans for substitutions. In addition, this paper introduces a pruning technique for eliminating redundant actions within a BDPO plan. We also evaluate our approach when combined with MaxSAT-based reorderings. Our experimental result demonstrates a significant improvement in plan execution flexibility on the benchmark problems from International Planning Competitions (IPC), maintaining good coverage and execution time.