A DRL method learns decentralized policies for multi-robot navigation from raw lidar in unknown environments via centralized training and decentralized execution.
Model-free reinforcement learning for fully cooperative multi-agent graphical games,
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End-to-end Decentralized Multi-robot Navigation in Unknown Complex Environments via Deep Reinforcement Learning
A DRL method learns decentralized policies for multi-robot navigation from raw lidar in unknown environments via centralized training and decentralized execution.