| 深度强化学习中稀疏奖励问题研究综述 (Survey on Sparse Reward in Deep Reinforcement Learning). W Ang, C Bai, C Cai, Y Zhao, P Liu 计算机科学 47 (3), 182-191, 2020 | 33 | 2020 |
| Variational dynamic for self-supervised exploration in deep reinforcement learning C Bai, P Liu, K Liu, L Wang, Y Zhao, L Han, Z Wang IEEE Transactions on neural networks and learning systems 34 (8), 4776-4790, 2021 | 13 | 2021 |
| Damped Anderson mixing for deep reinforcement learning: Acceleration, convergence, and stabilization K Sun, Y Wang, Y Liu, B Pan, S Jui, B Jiang, L Kong Advances in Neural Information Processing Systems 34, 3732-3743, 2021 | 12 | 2021 |
| Exploring the training robustness of distributional reinforcement learning against noisy state observations K Sun, Y Zhao, S Jui, L Kong Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 10 | 2023 |
| Generating attentive goals for prioritized hindsight reinforcement learning P Liu, C Bai, Y Zhao, C Bai, W Zhao, X Tang Knowledge-Based Systems 203, 106140, 2020 | 10 | 2020 |
| 深度 Q 学习的二次主动采样方法 赵英男， 刘鹏， 赵巍， 唐降龙 自动化学报 45 (10), 1870-1882, 2019 | 6 | 2019 |
| Exploring the robustness of distributional reinforcement learning against noisy state observations K Sun, Y Liu, Y Zhao, H Yao, S Jui, L Kong | 5 | 2021 |
| Distributional reinforcement learning via sinkhorn iterations K Sun, Y Zhao, Y Liu, W Liu, B Jiang, L Kong arXiv preprint arXiv:2202.00769, 2022 | 4 | 2022 |
| Obtaining accurate estimated action values in categorical distributional reinforcement learning Y Zhao, P Liu, C Bai, W Zhao, X Tang Knowledge-Based Systems 194, 105511, 2020 | 3 | 2020 |
| An exploratory rollout policy for imagination-augmented agents P Liu, Y Zhao, W Zhao, X Tang, Z Yang Applied Intelligence 49, 3749-3764, 2019 | 2 | 2019 |
| Variational Diversity Maximization for Hierarchical Skill Discovery Y Zhao, P Liu, W Zhao, X Tang Neural Processing Letters 55 (1), 839-855, 2023 | 1 | 2023 |
| Interpreting distributional reinforcement learning: A regularization perspective K Sun, Y Zhao, Y Liu, E Shi, Y Wang, X Yan, B Jiang, L Kong arXiv preprint arXiv:2110.03155, 2021 | 1 | 2021 |
| Towards understanding distributional reinforcement learning: Regularization, optimization, acceleration and sinkhorn algorithm K Sun, Y Zhao, Y Liu, E Shi, Y Wang, A Sadeghi, X Yan, B Jiang, L Kong | 1 | 2021 |
| Optimistic Exploration with Backward Bootstrapped Bonus for Deep Reinforcement Learning C Bai, L Wang, P Liu, Z Wang, HAO Jianye, Y Zhao | | 2020 |
