7 citations · 8 across the 4 of their papers we have counts for
4 papers
Effective Multi-Agent Deep Reinforcement Learning Control with Relative Entropy Regularization
Chenyang Miao, Yunduan Cui, Huiyun Li +1
In this paper, a novel Multi-agent Reinforcement Learning (MARL) approach, Multi-Agent Continuous Dynamic Policy Gradient (MACDPP) was proposed to tackle the issues of limited capa…
Practical Probabilistic Model-based Deep Reinforcement Learning by Integrating Dropout Uncertainty and Trajectory Sampling
Wenjun Huang, Yunduan Cui, Huiyun Li +1
This paper addresses the prediction stability, prediction accuracy and control capability of the current probabilistic model-based reinforcement learning (MBRL) built on neural net…
Uncertainty-aware Contact-safe Model-based Reinforcement Learning
Cheng-Yu Kuo, Andreas Schaarschmidt, Yunduan Cui +2
This letter presents contact-safe Model-based Reinforcement Learning (MBRL) for robot applications that achieves contact-safe behaviors in the learning process. In typical MBRL, we…
Reinforcement Learning Ship Autopilot: Sample efficient and Model Predictive Control-based Approach
Yunduan Cui, Shigeki Osaki, Takamitsu Matsubara
In this research we focus on developing a reinforcement learning system for a challenging task: autonomous control of a real-sized boat, with difficulties arising from large uncert…