12 citations · 60 across the 10 of their papers we have counts for
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cs.MA2022★ 7 cited
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration
Pengyi Li, Hongyao Tang, Tianpei Yang +8
Learning to collaborate is critical in Multi-Agent Reinforcement Learning (MARL). Previous works promote collaboration by maximizing the correlation of agents' behaviors, which is…
cs.LG2022★ 10 cited
Breaking the Curse of Dimensionality in Multiagent State Space: A Unified Agent Permutation Framework
Xiaotian Hao, Hangyu Mao, Weixun Wang +5
The state space in Multiagent Reinforcement Learning (MARL) grows exponentially with the agent number. Such a curse of dimensionality results in poor scalability and low sample eff…