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.

通过使用块去排序的策略，本研究提出了一种改进计划灵活性的方法，通过替换子计划中的行动来增加计划的灵活性，并通过消除冗余行动和优化重排策略的方式在国际规划竞赛 (IPC) 的基准问题上实验证明了该方法的显著改善。