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Conflict-Based Search for Multi Agent Path Finding with Asynchronous Actions

arXiv cs.AI / 3/20/2026

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Key Points

  • CBS-AA introduces Conflict-Based Search with Asynchronous Actions to solve MAPF with asynchronous actions, addressing CCBS incompleteness caused by continuous wait durations.
  • The method provides completeness and optimality guarantees for MAPF with asynchronous actions, bypassing the issue of uncountably infinite state spaces.
  • The authors propose conflict-resolution techniques to improve scalability, achieving up to a 90% reduction in branching.
  • By removing the synchronized-action assumption, the approach enables more practical multi-agent path planning in real-world asynchronous environments.

Abstract

Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from their respective start locations to their respective goal locations while minimizing path costs. Most existing MAPF algorithms rely on a common assumption of synchronized actions, where the actions of all agents start at the same time and always take a time unit, which may limit the use of MAPF planners in practice. To get rid of this assumption, Continuous-time Conflict-Based Search (CCBS) is a popular approach that can find optimal solutions for MAPF with asynchronous actions (MAPF-AA). However, CCBS has recently been identified to be incomplete due to an uncountably infinite state space created by continuous wait durations. This paper proposes a new method, Conflict-Based Search with Asynchronous Actions (CBS-AA), which bypasses this theoretical issue and can solve MAPF-AA with completeness and solution optimality guarantees. Based on CBS-AA, we also develop conflict resolution techniques to improve the scalability of CBS-AA further. Our test results show that our method can reduce the number of branches by up to 90%.