13 citations · 13 across the 4 of their papers we have counts for
5 papers
A Dynamics Perspective of Pursuit-Evasion Games of Intelligent Agents with the Ability to Learn
Hao Xiong, Huanhui Cao, Lin Zhang +1
Pursuit-evasion games are ubiquitous in nature and in an artificial world. In nature, pursuer(s) and evader(s) are intelligent agents that can learn from experience, and dynamics (…
Safe Multi-Agent Reinforcement Learning through Decentralized Multiple Control Barrier Functions
Zhiyuan Cai, Huanhui Cao, Wenjie Lu +2
Multi-Agent Reinforcement Learning (MARL) algorithms show amazing performance in simulation in recent years, but placing MARL in real-world applications may suffer safety problems.…
Modular Transfer Learning with Transition Mismatch Compensation for Excessive Disturbance Rejection
Tianming Wang, Wenjie Lu, Huan Yu +1
Underwater robots in shallow waters usually suffer from strong wave forces, which may frequently exceed robot's control constraints. Learning-based controllers are suitable for dis…
A2: Extracting Cyclic Switchings from DOB-nets for Rejecting Excessive Disturbances
Wenjie Lu, Dikai Liu
Reinforcement Learning (RL) is limited in practice by its gray-box nature, which is responsible for insufficient trustiness from users, unsatisfied interpretation for human interve…
DOB-Net: Actively Rejecting Unknown Excessive Time-Varying Disturbances
Tianming Wang, Wenjie Lu, Zheng Yan +1
This paper presents an observer-integrated Reinforcement Learning (RL) approach, called Disturbance OBserver Network (DOB-Net), for robots operating in environments where disturban…