most citedRevisiting QMIX: Discriminative Credit Assignment by Gradient Entropy Regularization

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI20221 cited

DouZero+: Improving DouDizhu AI by Opponent Modeling and Coach-guided Learning

Youpeng Zhao, Jian Zhao, Xunhan Hu +2

Recent years have witnessed the great breakthrough of deep reinforcement learning (DRL) in various perfect and imperfect information games. Among these games, DouDizhu, a popular c…

cs.LG20221 cited

Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents

Jian Zhao, Youpeng Zhao, Weixun Wang +5

Multi-agent reinforcement learning is difficult to be applied in practice, which is partially due to the gap between the simulated and real-world scenarios. One reason for the gap…

cs.MA20221 cited

CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement Learning

Jian Zhao, Xunhan Hu, Mingyu Yang +3

Due to the partial observability and communication constraints in many multi-agent reinforcement learning (MARL) tasks, centralized training with decentralized execution (CTDE) has…

cs.AI20223 cited

Revisiting QMIX: Discriminative Credit Assignment by Gradient Entropy Regularization

Jian Zhao, Yue Zhang, Xunhan Hu +5

In cooperative multi-agent systems, agents jointly take actions and receive a team reward instead of individual rewards. In the absence of individual reward signals, credit assignm…

cs.LG2022

MCMARL: Parameterizing Value Function via Mixture of Categorical Distributions for Multi-Agent Reinforcement Learning

Jian Zhao, Mingyu Yang, Youpeng Zhao +4

In cooperative multi-agent tasks, a team of agents jointly interact with an environment by taking actions, receiving a team reward and observing the next state. During the interact…