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

Xuemian Wu, Shizhe Zhao, Zhongqiang Ren
3/19/2026
cs.AI

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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%.

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@article{wu2026conflictbased,
  title  = {Conflict-Based Search for Multi Agent Path Finding with Asynchronous Actions},
  author = {Xuemian Wu and Shizhe Zhao and Zhongqiang Ren},
  year   = {2026},
  eprint = {2603.18866},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2603.18866v1}
}

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