Improving Plan Execution Flexibility using Block-Substitution
<|reference_start|>Improving Plan Execution Flexibility using Block-Substitution: 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.<|reference_end|>
@article{noor2024improving,
    title={Improving Plan Execution Flexibility using Block-Substitution},
    author={Sabah Binte Noor and Fazlul Hasan Siddiqui},
    journal={arXiv preprint arXiv:2406.03091},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.03091},
    primaryClass={cs.AI}
}