发表论文
(1) Yingnan Zhao，Peng Liu, Chenjia Bai, Wei Zhao*, Xianglong Tang. Obtaining accurate estimated action values in categorical distributional reinforcement learning[J]. Knowledge-Based Systems, 2020, 194: 105511. CCF-C, IF=8.139
(2) Peng Liu, Yingnan Zhao, Wei Zhao*, Xianglong Tang，Zichan Yang. An exploratory rollout policy for imagination-augmented agents[J]. Applied Intelligence，2019，49（10）：3749-3764. CCF-C, IF=5.019
(3) Ke Sun, Yingnan Zhao, Linglong Kong* et al. Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observation. ECML-PKDD, 2023. CCF-B会议.
(4) 赵英男,刘鹏,赵巍*,唐降龙. 深度 Q 学习的二次主动采样方法[J].自动化学报, 2019, 45 (10): 1870 - 1882. CCF-A中文期刊，IF=3.508.
(5) Yingnan Zhao, Peng Liu, Wei Zhao. et al. Variational Diversity Maximization for Hierarchical Skill Discovery. Neural Process Lett 55, 839–855 (2023). CCF-C, IF=3.1.
(6) Chenjia Bai, Peng Liu, Yingnan Zhao, et al. Generating attentive goals for prioritized hindsight reinforcement learning[J]. Knowledge-Based Systems, 203: 106140 (2020). CCF-C, IF=8.139.
(7) Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, et al. Damped Anderson mixing for deep reinforcement learning: Acceleration, convergence, and stabilization[J]. Advances in Neural Information Processing Systems, 34: 3732-3743 (2021). CCF-A会议.
(8) Chenjia Bai, Peng Liu, Kaiyu Liu, Yingnan Zhao, et al. Variational dynamic for self-supervised exploration in deep reinforcement learning[J]. IEEE Transactions on neural networks and learning systems, 34: 4776-4790, (2021). CCF-B，IF=10.4.
