Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization. - Qi Zhou 008; Houqiang Li; Jie Wang 005 (AAAI, 2020)

Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization Method. - Qi Zhou 008; Yufei Kuang; Zherui Qiu; Houqiang Li; Jie Wang 005 (NeurIPS, 2020)

Learning Robust Policy against Disturbance in Transition Dynamics via State-Conservative Policy Optimization. - Yufei Kuang; Miao Lu; Jie Wang 005; Qi Zhou 008; Bin Li 025; Houqiang Li (AAAI, 2022)

Sample-Efficient Reinforcement Learning via Conservative Model-Based Actor-Critic. - Zhihai Wang; Jie Wang 005; Qi Zhou 008; Bin Li 025; Houqiang Li (AAAI, 2022)

Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions. - Qiyuan Liu 008; Qi Zhou 008; Rui Yang 031; Jie Wang 005 (AAAI, 2023)

Efficient Exploration in Resource-Restricted Reinforcement Learning. - Zhihai Wang; Taoxing Pan; Qi Zhou 008; Jie Wang 005 (AAAI, 2023)

Learning robust representation for reinforcement learning with distractions by reward sequence prediction. - Qi Zhou 008; Jie Wang 005; Qiyuan Liu 008; Yufei Kuang; Wengang Zhou 001; Houqiang Li (UAI, 2023)

Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution. - Jie Wang 005; Rui Yang 031; Zijie Geng; Zhihao Shi; Mingxuan Ye; Qi Zhou 008; Shuiwang Ji; Bin Li 025; Yongdong Zhang 001; Feng Wu 001 (CoRR, 2023)