7 citations · 9 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
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…
Sample-Efficient Multi-Agent Reinforcement Learning with Demonstrations for Flocking Control
Yunbo Qiu, Yuzhu Zhan, Yue Jin +2
Flocking control is a significant problem in multi-agent systems such as multi-agent unmanned aerial vehicles and multi-agent autonomous underwater vehicles, which enhances the coo…
Sub-optimal Policy Aided Multi-Agent Reinforcement Learning for Flocking Control
Yunbo Qiu, Yue Jin, Jian Wang +1
Flocking control is a challenging problem, where multiple agents, such as drones or vehicles, need to reach a target position while maintaining the flock and avoiding collisions wi…
Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning
Yue Jin, Shuangqing Wei, Jian Yuan +1
In multi-agent deep reinforcement learning, extracting sufficient and compact information of other agents is critical to attain efficient convergence and scalability of an algorith…
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…