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Autores principales: Wu, Xuemian, Zhao, Shizhe, Ren, Zhongqiang
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2603.18866
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author Wu, Xuemian
Zhao, Shizhe
Ren, Zhongqiang
author_facet Wu, Xuemian
Zhao, Shizhe
Ren, Zhongqiang
contents 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%.
format Preprint
id arxiv_https___arxiv_org_abs_2603_18866
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Conflict-Based Search for Multi Agent Path Finding with Asynchronous Actions
Wu, Xuemian
Zhao, Shizhe
Ren, Zhongqiang
Artificial Intelligence
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%.
title Conflict-Based Search for Multi Agent Path Finding with Asynchronous Actions
topic Artificial Intelligence
url https://arxiv.org/abs/2603.18866