I am currently a fourth-year Ph.D. student at Tsinghua Shenzhen International Graduate School, Tsinghua University supervised by Prof. Xiu Li. I am now working as a group leader of Reinforcement Learning Group of Intelligent Computing Lab (ICLAB). I receive my bachelor’s degree from the Department of Engineering Physics, Tsinghua University in 2020.

I am fortunate to work closely with Prof. Zongqing Lu from Peking University. I am now an intern student at Game AI Research Center, Tencent IEG (Interactive Entertainment Group), supervised by Mr. Le Wan and Mr. Jingwen Yang. Before that, I was an intern student at Pengcheng Lab (PCL) supervised by Prof. Zongqing Lu.

My research interests lie in efficient decision-making with deep Reinforcement Learning, including offline RL, sample-efficient general online model-free RL, and model-based RL. Meanwhile, I am interested in deploying RL algorithms in real-world applications, such as robotics, traffic signal control, etc.

Please feel free to drop me an e-mail if you are interested in collaborating with me. lvjf20[AT]mails.tsinghua.edu.cn

Publications

Preprints

• Bias-reduced Multi-step Hindsight Experience Replay for Efficient Multi-goal Reinforcement Learning. Rui Yang, Jiafei Lyu, Yu Yang, Jiangpeng Yan, Feng Luo, Dijun Luo, Lanqing Li, Xiu Li.
• The Primacy Bias in Model-based RL. Zhongjian Qiao, Jiafei Lyu, Xiu Li.
• Exploration and Anti-Exploration with Distributional Random Network Distillation. Kai Yang, Jian Tao, Jiafei Lyu, Xiu Li.
• Understanding What Affects Generalization Gap in Visual Reinforcement Learning: Theory and Empirical Evidence. Jiafei Lyu, Le Wan, Xiu Li and Zongqing Lu.

Conference Papers

• Efficient Continuous Control with Double Actors and Regularized Critics. Jiafei Lyu^*，Xiaoteng Ma^*, Jiangpeng Yan, Xiu Li. AAAI Conference on Artificial Intelligence, (AAAI), 2022. (Oral)
• Double Check Your State Before Trusting It: Confidence-Aware Bidirectional Offline Model-Based Imagination. Jiafei Lyu, Xiu Li, Zongqing Lu. Advances in Neural Information Processing Systems (NeurIPS), 2022. (Spotlight)
• Mildly Conservative Q-learning for Offline Reinforcement Learning. Jiafei Lyu^*, Xiaoteng Ma^*, Xiu Li, Zongqing Lu. Advances in Neural Information Processing Systems (NeurIPS), 2022. (Spotlight)
• PRAG: Periodic Regularized Action Gradient for Efficient Continuous Control. Xihui Li, Zhongjian Qiao, Aicheng Gong, Jiafei Lyu, Chenghui Yu, Jiangpeng Yan, Xiu Li. Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2022.
• Uncertainty-driven Trajectory Truncation for Data Augmentation in Offline Reinforcement Learning. Junjie Zhang^*, Jiafei Lyu^*, Xiaoteng Ma, Jiangpeng Yan, Jun Yang, Le Wan, Xiu Li. European Conference on Artificial Intelligence (ECAI), 2023. (Oral)
• Normalization Enhances Generalization in Visual Reinforcement Learning. Lu Li^*, Jiafei Lyu^*, Guozheng Ma, Zilin Wang, Zhenjie Yang, Xiu Li, Zhiheng Li. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024. (Oral). Generalization in Planning Workshop at NeurIPS, 2023.
• Towards Understanding How to Reduce Generalization Gap in Visual Reinforcement Learning. Jiafei Lyu, Le Wan, Xiu Li and Zongqing Lu. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024 (Extended Abstract).
• SEABO: A Simple Search-Based Method for Offline Imitation Learning. Jiafei Lyu, Xiaoteng Ma, Le Wan, Runze Liu, Xiu Li, Zongqing Lu. International Conference on Learning Representations (ICLR), 2024.
• Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model. Kai Yang, Jian Tao, Jiafei Lyu, Chunjiang Ge, Jiaxin Chen, Qimai Li, Weihan Shen, Xiaolong Zhu, Xiu Li. IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024

Journal Papers

• Value Activation for Bias Alleviation: Generalized-activated Deep Double Deterministic Policy Gradients. Jiafei Lyu^*, Yu Yang^*, Jiangpeng Yan, Xiu Li. Neurocomputing, 2023. (IF=5.7)
• Off-Policy RL Algorithms Can be Sample-Efficient for Continuous Control via Sample Multiple Reuse. Jiafei Lyu, Le Wan, Zongqing Lu, Xiu Li. Information Sciences, 2024. (IF=8.1)

Workshop Papers

• State Advantage Weighting for Offline RL. Jiafei Lyu, Aicheng Gong, Le Wan, Zongqing Lu, Xiu Li. ICLR 2023 tiny paper, 3rd Offline RL Workshop: Offline RL as a ‘‘Launchpad’’ at NeurIPS, 2022.
• Zero-shot Preference Learning for Offline RL via Optimal Transport. Runze Liu, Yali Du, Fengshuo Bai, Jiafei Lyu, Xiu Li. Optimal Transport and Machine Learning Workshop at NeurIPS, 2023.

Collaborators

• Xiu Li: Professor, Tsinghua Shenzhen International Graduate School, Tsinghua University
• Zongqing Lu: BOYA Assistant Professor, School of Computer Science, Peking University
• Xiaoteng Ma: Ph.D. student, Department of Automation, Tsinghua University
• Jiangpeng Yan: Top minds, Huawei (Ph.D. alumni of Department of Automation, Tsinghua University)
• Rui Yang: Ph.D. Student, Department of Computer Science and Engineering (CSE), Hong Kong University of Science and Technology.

Honors

• 2018.10 Academic Excellence Award of Tsinghua University
• 2021.10 Outstanding Scholarship of Tsinghua University
• 2022.10 Outstanding Scholarship of Tsinghua University
• 2023.07 Recognition Award of 2022 Tencent Rhino-Bird Research Elite Program
• 2023.10 Outstanding Scholarship of Tsinghua University

Educations

• 2020 - present, Ph.D., Tsinghua Shenzhen International Graduate School, Tsinghua University
• 2017 - 2020, Minor in Statistics, Center for Statistical Science, Tsinghua University
• 2016 - 2020, Bachelor, Department of Engineering Physics, Tsinghua University

Internships

• Tencent IEG, Game AI Research Center (2023.10 - present)

  Research on offline RL, transfer RL

• Tencent IEG, Game AI Research Center (2022.06 - 2023.10)

  Researched on offline RL, sample-efficient online RL, and offline2online RL

• Pengcheng Lab (2021.10 - 2022.04)

  Researched on offline RL

Teaching

• Machine Learning by Prof. Xuegong Zhang, Autumn 2020. (Teaching Assistant)
• Frontier of AI Technology and Industrial Application by Prof. Xiu Li, Autumn 2021. (Teaching Assistant)

Services

• Conference Reviewer: ICML (2022, 2023, 2024), NeurIPS (2022, 2023), AAAI (2022, 2023, 2024), ECAI (2023), ICLR (2024), RLC (2024)
• Journal Reviewer: TMLR