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A Collection of Multi-Agent Reinforcement Learning (MARL) Resources

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MARL Resources Collection

This is a collection of Multi-Agent Reinforcement Learning (MARL) Resources. The purpose of this repository is to give beginners a better understanding of MARL and accelerate the learning process. Note that some of the resources are written in Chinese and only important papers that have a lot of citations were listed.

I will continually update this repository and I welcome suggestions. (missing important papers, missing important resources, invalid links, etc.) This is only a first draft so far and I'll add more resources in the next few months.

This repository is not for commercial purposes.

My email: chenhao915@mails.ucas.ac.cn

Overview

Courses

Important Conferences

  • AAMAS, AAAI, IJCAI, ICLR, ICML, NIPS
  • Sorted by difficulty (roughly)

Reviews

Recent Reviews (Since 2019)

Other Reviews (Before 2019)

Books

Open Source Environments

Research Groups

Organization Reaearcher Lab homepage (if any)
Oxford Shimon Whiteson, Jakob N. Foerster link
University College London (UCL) Jun Wang
Tsinghua University (THU) Chongjie Zhang link
Tsinghua University (THU) Yi Wu
Peking University (PKU) Zongqing Lu
HUAWEI Hangyu Mao
Nanjing University (NJU) Yang Yu
Facebook Yuandong Tian
Tianjin University (TJU) Jianye Hao link
University of Illinois at Urbana-Champaign (UIUC) Kaiqing Zhang
Peking University (PKU) Yaodong Yang Link
Nanyang Technological University (NTU) Bo An
Shanghai Jiao Tong University (SJTU) Weinan Zhang link
University of Chinese Academy of Sciences (UCAS) Haifeng Zhang link
University of Edinburgh Stefano V. Albrecht link GitHub
University College London (UCL) UCL Deciding, Acting, and Reasoning with Knowledge (DARK) Lab Link
University of Maryland Furong Huang Link

Companies

Paper Lists

Talks

In English

In Chinese

Useful Resources

In English

In Chinese

TODO

  • The Research Groups part needs to be completed
  • The Companies part needs to be completed
  • The Useful Resources part needs to be perfected

Citation

If you find this repository useful, please cite our repo:

@misc{chen2021collection,
  author={Chen, Hao},
  title={A Collection of Multi-Agent Reinforcement Learning Resources},
  year={2021}
  publisher = {GitHub},
  journal = {GitHub Repository},
  howpublished = {\url{https://github.com/TimeBreaker/MARL-resources-collection}}
}

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