9 citations · 23 across the 11 of their papers we have counts for
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cs.LG2021★ 5 cited
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning
Weichao Mao, Lin F. Yang, Kaiqing Zhang +1
Multi-agent reinforcement learning (MARL) algorithms often suffer from an exponential sample complexity dependence on the number of agents, a phenomenon known as \emph{the curse of…
cs.LG2021
Provably Efficient Reinforcement Learning in Decentralized General-Sum Markov Games
Weichao Mao, Tamer Başar
This paper addresses the problem of learning an equilibrium efficiently in general-sum Markov games through decentralized multi-agent reinforcement learning. Given the fundamental…