1 citations · 1 across the 6 of their papers we have counts for
6 papers
Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games
Bingyu Hui, Lebin Yu, Quanming Yao +3
Zero-shot coordination(ZSC), a key challenge in multi-agent game theory, has become a hot topic in reinforcement learning (RL) research recently, especially in complex evolving gam…
Robust Communicative Multi-Agent Reinforcement Learning with Active Defense
Lebin Yu, Yunbo Qiu, Quanming Yao +3
Communication in multi-agent reinforcement learning (MARL) has been proven to effectively promote cooperation among agents recently. Since communication in real-world scenarios is…
Promoting Cooperation in Multi-Agent Reinforcement Learning via Mutual Help
Yunbo Qiu, Yue Jin, Lebin Yu +2
Multi-agent reinforcement learning (MARL) has achieved great progress in cooperative tasks in recent years. However, in the local reward scheme, where only local rewards for each a…
Improving Zero-Shot Coordination Performance Based on Policy Similarity
Lebin Yu, Yunbo Qiu, Quanming Yao +2
Over these years, multi-agent reinforcement learning has achieved remarkable performance in multi-agent planning and scheduling tasks. It typically follows the self-play setting, w…
Low Entropy Communication in Multi-Agent Reinforcement Learning
Lebin Yu, Yunbo Qiu, Qiexiang Wang +2
Communication in multi-agent reinforcement learning has been drawing attention recently for its significant role in cooperation. However, multi-agent systems may suffer from limita…
Robust Reinforcement Learning under model misspecification
Lebin Yu, Jian Wang, Xudong Zhang
Reinforcement learning has achieved remarkable performance in a wide range of tasks these days. Nevertheless, some unsolved problems limit its applications in real-world control. O…