Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination

ICLR 2020 Shauharda KhadkaSomdeb MajumdarSantiago MiretStephen McAleerKagan Tumer

Many cooperative multiagent reinforcement learning environments provide agents with a sparse team-based reward, as well as a dense agent-specific reward that incentivizes learning basic skills. Training policies solely on the team-based reward is often difficult due to its sparsity... (read more)

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