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Anytime Single-Step MAPF Planning with Anytime PIBT

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arxiv 2504.07841 v1 pith:7QY6SUJ4 submitted 2025-04-10 cs.AI cs.MA

classification cs.AIcs.MA
keywords pibtsolutionanytimesingle-stepmapfqualityfindfinds
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PIBT is a popular Multi-Agent Path Finding (MAPF) method at the core of many state-of-the-art MAPF methods including LaCAM, CS-PIBT, and WPPL. The main utility of PIBT is that it is a very fast and effective single-step MAPF solver and can return a collision-free single-step solution for hundreds of agents in less than a millisecond. However, the main drawback of PIBT is that it is extremely greedy in respect to its priorities and thus leads to poor solution quality. Additionally, PIBT cannot use all the planning time that might be available to it and returns the first solution it finds. We thus develop Anytime PIBT, which quickly finds a one-step solution identically to PIBT but then continuously improves the solution in an anytime manner. We prove that Anytime PIBT converges to the optimal solution given sufficient time. We experimentally validate that Anytime PIBT can rapidly improve single-step solution quality within milliseconds and even find the optimal single-step action. However, we interestingly find that improving the single-step solution quality does not have a significant effect on full-horizon solution costs.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding

    cs.RO 2026-02 conditional novelty 6.0 of 10

    ACCBS is a closed-loop CBS variant whose planning horizon grows with the available computation budget while reusing a single constraint tree, giving anytime behavior and conditional asymptotic optimality.

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