Limb-as-agent MAPPO with a shared global critic speeds up humanoid walking policy training and improves gait smoothness over single-agent PPO in simulation and on hardware.
Learning vision-based bipedal locomotion for challeng- ing terrain,
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MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotion
Limb-as-agent MAPPO with a shared global critic speeds up humanoid walking policy training and improves gait smoothness over single-agent PPO in simulation and on hardware.