Jianlin Mao

Mean-Field Deep Reinforcement Learning for Multi-Agent Path Finding

Continuous-space multi-agent path finding (MAPF) presents severe challenges for deep reinforcement learning (DRL), as joint state–action spaces grow exponentially and fine-grained inter-agent coordination is required. Applying mean-field approximation can reduce input complexity from <inline-formula