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

2026-03-19

AI Summary

This work proposes CBS-AA, a novel approach to address the incompleteness of existing algorithms in multi-agent pathfinding caused by asynchronous actions. CBS-AA is the first method to achieve complete and optimal solutions for asynchronous multi-agent path planning without assuming synchronized actions, effectively overcoming the challenge of uncountable state spaces induced by continuous waiting times. By integrating a conflict-based search framework with an efficient mechanism for resolving asynchronous conflicts, the algorithm significantly enhances scalability. Experimental results demonstrate that CBS-AA reduces the number of search branches by up to 90% compared to baseline methods, leading to substantial improvements in solving efficiency.

Technology Category

• Multiagent Systems: Multiagent Planning
• Search and Optimization: Adversarial Search
• Planning, Routing, and Scheduling: Learning for Planning and Scheduling

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

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%.

Problem

• Multi-Agent Path Finding
• Asynchronous Actions
• Conflict-Based Search
• Continuous-time Planning
• Path Planning

Innovation

• Conflict-Based Search
• Asynchronous Actions
• Multi-Agent Path Finding
• Completeness
• Optimality