Two papers about fine-tuning LLMs for decision-making tasks, AdaRefiner and LLaMA-Rider, were accepted at NAACL’24.

Three papers respectively on LMMs, policy pre-training and offline RL were accepted at ICLR’24. Additionally, we have one paper accepted at TMLR, two at AAAI’24, and two at AAMAS’24. Congratulations to all.

Our two papers about learning from observation and multi-agent reinforcement learning were accepted at NeurIPS’23. Congratulations to Bohan and Jiangxing.

Recent Publications

More Publications

Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Findings, June 16–21, 2024.

Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Findings, June 16–21, 2024.

Eighth International Conference on Learning Representations (ICLR), May 7-11, 2024. (Acceptance Rate: 1.2%, oral)

Recently developed foundation models, such as large language models and multi-modal models, open great opportunities to build generally capable agents, combined with reinforcement learning. This project focuses on learning skills and foundation models and connecting them to build generalist agents. In the following, we introduce some of our studies. For more details, please refer to the papers. Plan4MC We study building a multi-task agent in Minecraft. Without human demonstrations, solving long-horizon tasks in this open-ended environment with reinforcement learning (RL) is extremely sample inefficient. [Read More…]


Multi-Agent Reinforcement Learning (MARL) has recently attracted much attention from the communities of machine learning, artificial intelligence, and multi-agent systems. As an interdisciplinary research field, there are so many unsolved problems, from cooperation to competition, from agent communication to agent modeling, from centralized learning to decentralized learning. MARL has been the main research focus of our lab. We are investigating the field from many perspectives. In the following, we introduce some of our studies. [Read More…]


Teaching

Undergraduate Courses

  • Algorithms, Spring 2019, 2020, 2021, 2022
  • Data Structures and Algorithms, Spring 2018
  • Introduction to Computer Systems, Fall 2017

Gradudate Courses

  • Deep Reinforcement Learning, Spring 2020, 2021, 2022, 2023, 2024

Services

Editorship and Area Chair

  • Associate Editor, ACM Journal on Autonomous Transportation Systems, 2022 -

  • Guest Editor, Machine Learning Special Issue on RL for Real Life, 2023

  • Area Chair, ICLR 2024, ICML 2024

Conference Organization

  • IEEE Conference on Games 2022, Keynote Co-Chair

  • ICML 2021 Workshop on Reinforcement Learning for Real Life, General Co-Chair

  • INFOCOM 2020 Worksop on Network Intelligence, General Co-Chair

  • ACM TURC 2018, Award Co-Chair

Program Committee Member (Reviewer)

  • ICLR 2023 2022 2021 2020, NeurIPS 2023 2022 2021 2020, ICML 2023 2022 2021, AAAI 2022, IJCAI 2022 2021 2020, AAMAS 2020, CoRL 2020
  • Nature Machine Intelligence

Contact

  • Room 523, Yanyuan Building, Peking University, Beijing, 100871, China.

  • Office hour: please drop me an email to schedule