Preprint
Aug 2026
Search-Aided Joint Agent-Environment Reinforcement Learning for Robust Lifelong Multi-Agent Path Finding with Rotations
This work introduces a unified RL formulation that jointly optimizes agent and environment policies, where the environment policy learns graph edge costs to provide global movement guidance via backward Dijkstra search and achieves significant improvements over the strong search-based planner, Causal-PIBT, across multi...
He Jiang, Jingtian Yan, Yulun Zhang et al.
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