Mutex Propagation in Multi-Agent Path Finding for Large Agents

Han Zhang, Yutong Li, Jiaoyang Li, T. K. S. Kumar, Sven Koenig
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Abstract

Mutex propagation and its concomitant symmetry-breaking techniques have proven useful in Multi-Agent Path Finding (MAPF) with point agents. In this paper, we show that they can be easily generalized to richer MAPF problems. In particular, we demonstrate their application to MAPF with ``Large'' Agents (LA-MAPF). Here, agents can occupy multiple points at the same time according to their fixed shapes and sizes. While existing rule-based symmetry-breaking techniques are difficult to generalize from point agents to large agents, mutex-based symmetry-breaking techniques can be generalized easily. In a Conflict-Based Search (CBS) framework for LA-MAPF, we also develop a mutex-based conflict-selection strategy to further enhance the efficiency of the search. Through experiments on various maps, we show that our techniques significantly improve MC-CBS, a state-of-the-art optimal LA-MAPF algorithm, in terms of both success rate and runtime.
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大型智能体多智能体寻径中的互斥体传播
互斥量传播及其相关的对称性破坏技术在点智能体的多智能体寻径(MAPF)中被证明是有用的。在本文中,我们证明了它们可以很容易地推广到更丰富的MAPF问题。特别地,我们展示了它们在具有“大”代理(LA-MAPF)的MAPF中的应用。在这里,代理可以根据其固定的形状和大小同时占据多个点。现有的基于规则的对称破坏技术很难从点代理推广到大型代理,而基于互斥体的对称破坏技术可以很容易地推广。在基于冲突的LA-MAPF搜索框架中,我们还开发了一种基于互斥体的冲突选择策略,以进一步提高搜索效率。通过在各种地图上的实验,我们表明我们的技术在成功率和运行时间方面显著提高了MC-CBS,这是一种最优的LA-MAPF算法。
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