
TL;DR
This paper investigates the computational complexity of modifying action orderings in plans to optimize constraints and parallel execution time, revealing NP-hardness results and identifying tractable cases within certain planning languages.
Contribution
It introduces three new criteria for reordering plans, analyzes their computational complexity, and identifies classes of planning languages where optimal deordering can be computed efficiently.
Findings
Weakest criterion is tractable, others are NP-hard.
Optimal deorderings are polynomial-time computable in certain planning languages.
Reordering for faster parallel execution remains NP-hard and hard to approximate.
Abstract
This article studies the problem of modifying the action ordering of a plan in order to optimise the plan according to various criteria. One of these criteria is to make a plan less constrained and the other is to minimize its parallel execution time. Three candidate definitions are proposed for the first of these criteria, constituting a sequence of increasing optimality guarantees. Two of these are based on deordering plans, which means that ordering relations may only be removed, not added, while the third one uses reordering, where arbitrary modifications to the ordering are allowed. It is shown that only the weakest one of the three criteria is tractable to achieve, the other two being NP-hard and even difficult to approximate. Similarly, optimising the parallel execution time of a plan is studied both for deordering and reordering of plans. In the general case, both of these…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
