Our two papers “The Emergence of Individuality” and “FOP: Factorizing Optimal Joint Policy of Maximum-Entropy Multi-Agent Reinforcement Learning” were accepted at ICML’21.

Our paper “Learning Individually Inferred Communication for Multi-Agent Cooperation” was accepted at NIPS’20 for oral presentation. Congratulations to Ziluo Ding.

Our paper “Graph Convolutional Reinforcement Learning” was accepted at ICLR’20. Congratulations to Jiechuan Jiang.

Recent Publications

More Publications

Thirty-Eighth International Conference on Machine Learning (ICML), July 18-24, 2021 (Acceptance Rate: 3%=1665513, oral presentation)

Thirty-Eighth International Conference on Machine Learning (ICML), July 18-24, 2021 (Acceptance Rate: 21%=11845513)

Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), February 2-9, 2021. (Acceptance Rate: 21%=16927911)

AI@edge Lab

More Details

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…]

Reinforcement learning (RL) has the potential be applied to many real-world applications. In our research, we also investigate the applications of RL and Multi-agent RL. Currently, we have been investigating two applications: one is traffic signal control; another is EDA. Traffic signals coordinating traffic movements are the key for transportation efficiency. However, conventional traffic signal control that heavily relies on pre-defined rules and assumptions on traffic conditions is far from intelligence. [Read More…]


Undergraduate Courses

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

Gradudate Courses

  • Deep Reinforcement Learning, Spring 2022
  • Deep RL and Multi-Agent RL, Spring 2020, 2021


Program Committee Member (Reviewer)

  • ICLR 2022 2021, NeurIPS 2021 2020, ICML 2021, CoRL 2020, IJCAI 2020 2021, AAMAS 2020, INFOCOM 2016 2019 2020, MM 2017 2018

  • Nature Machine Intelligence

Conference Organization

  • 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


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

  • Office hour: please drop me an email to schedule