Distributed Heuristic Multi-Agent Path Finding with Communication
Ziyuan Ma,Yudong Luo,Hang Ma,Ziyuan Ma,Yudong Luo,Hang Ma
Multi-Agent Path Finding (MAPF) is essential to large-scale robotic systems. Recent methods have applied reinforcement learning (RL) to learn decentralized polices in partially observable environments. A fundamental challenge of obtaining collision-free policy is that agents need to learn co-operation to handle congested situations. This paper combines communication with deep Q-learning to provide...
