Tutorial4RL

Tutorial4RL: Tutorial for Reinforcement Learning. 强化学习入门教程.

Related Repository

| Repository | Remark | | ------------------------------------------------------------ | ------------------------------------------------------------ | | Awesome-Reinforcement-Learning-Papers | <a href="https://github.com/Allenpandas/Awesome-Reinforcement-Learning-Papers"><img alt="GitHub repo size" src="https://img.shields.io/github/repo-size/Allenpandas/Awesome-Reinforcement-Learning-Papers"></a> <a href="https://github.com/Allenpandas/Awesome-Reinforcement-Learning-Papers"><img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/Allenpandas/Awesome-Reinforcement-Learning-Papers"></a> <a href="https://github.com/Allenpandas/Awesome-Reinforcement-Learning-Papers"><img alt="GitHub last commit (by committer)" src="https://img.shields.io/github/last-commit/Allenpandas/Awesome-Reinforcement-Learning-Papers"></a> | | Tutorial4RL | <a href="https://github.com/Allenpandas/Tutorial4RL"><img alt="GitHub repo size" src="https://img.shields.io/github/repo-size/Allenpandas/Tutorial4RL"></a> <a href="https://github.com/Allenpandas/Tutorial4RL"><img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/Allenpandas/Tutorial4RL"></a> <a href="https://github.com/Allenpandas/Tutorial4RL"><img alt="GitHub last commit (by committer)" src="https://img.shields.io/github/last-commit/Allenpandas/Tutorial4RL"></a> |

Open Source Projects

• PFRL：基于Pytorch的深度强化学习库： https://github.com/pfnet/pfrl
• 莫烦强化学习TensorFlow代码： https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow
• 百度飞桨PaddlePaddle强化学习代码： https://github.com/PaddlePaddle/PARL
• Github强大的强化学习库： https://github.com/wwxFromTju/awesome-reinforcement-learning-lib
• 优达学城（在线教育平台）强化学习库： https://github.com/udacity/deep-reinforcement-learning

Books & Videos

• 《深度强化学习》王树森： https://www.bilibili.com/video/BV12o4y197US
• 《Deep Reinforcement Learning》李宏毅： https://www.bilibili.com/video/BV1UE411G78S
• 《世界冠军带你从零实践强化学习》百度飞桨团队： https://www.bilibili.com/video/BV1yv411i7xd
• 《强化学习白板推导》：https://space.bilibili.com/97068901/channel/seriesdetail?sid=594040
• 《蘑菇书EasyRL》王琦等： https://github.com/datawhalechina/easy-rl
• 《动手学强化学习》张伟楠等： http://hrl.boyuai.com/

Relevant Conferences

| Abbr. | Full Name | CCF Rank | | ------- | ------------------------------------------------------------ | :------: | | ICML | International Conference on Machine Learning | CCF-A | | NeurIPS | Annual Conference on Neural Information Processing Systems | CCF-A | | ICLR | International Conference on Learning Representations | — | | AAAI | AAAI Conference on Artificial Intelligence | CCF-A | | IJCAI | International Joint Conference on Artificial Intelligence | CCF-A | | AAMAS | International Joint Conference on Autonomous Agents and Multi-agent Systems | CCF-B | | ICRA | IEEE International Conference on Robotics and Automation | CCF-B |

Community

• RLChina强化学习社区： http://rlchina.org/
• 智源社区强化学习专栏： https://hub.baai.ac.cn/?tag_id=74
• 智源社区强化学习周刊： https://hub.baai.ac.cn/users/18447

Langya Rank

Domestic Langya Rank

| Name | Organization | Link | Focus | | ------ | ------------------ | --------------------------------------------------------- | ---------------------------------------- | | 郝建业 | 天津大学 | [HomePage] | 多智能体强化学习、博弈论 | | 张海峰 | 中科院自动化所 | [HomePage] | 多智能体强化学习、智能体博弈、智能体评估 | | 罗军 | 华为诺亚方舟实验室 | [HomePage] | 自动驾驶、强化学习 | | 王祥丰 | 华东师范大学 | [HomePage] | 多智体强化学习 | | 俞扬 | 南京大学 | [HomePage] | 强化学习、离线强化学习 | | 杨耀东 | 北京大学 | [HomePage] | 多智能体强化学习、博弈论 | | 卢宗青 | 北京大学 | [HomePage] | 强化学习 | | 张崇洁 | 清华大学 | [HomePage] | 深度强化学习、多智能体 |

Abroad Langya Rank

| Name | Organization | Link | | -------------------- | ------------------------------------------------------------ | :----------------------------------------------------------: | | Sergey Levine | UC Berkeley | [Google Scholar] | | Piter Abbeel | UC Berkeley | [Google Scholar] | | Matthew E. Taylor | University of Alberta | [Google Scholar] | | Peter Stone | University of Texas at Austin | [Google Scholar] | | Shimon Whiteson | University of Oxford / Waymo | [Google Scholar] | | Jan Peters | German AI Research Center | [Google Scholar] | | Shie Mannor | Nvidia | [Google Scholar] | | Chelsea Finn | Stanford University / Google | [Google Scholar] | | Dusit Niyato | | [Google Scholar] | | Doina Precup | DeepMind / McGill University | [Google Scholar] | | Ann Nowé | | [Google Scholar] | | Marcello Restelli | Politecnico di Milano | [Google Scholar] | | Frank L. Lewis | | [Google Scholar] | | H. Vincent Poor | | [Google Scholar] | | Vaneet Aggarwal | Purdue University | [Google Scholar] | | F. Richard Yu | Carleton University | [Google Scholar] | | Jun Wang | University College London | [Google Scholar] | | Michael L. Littman | | [Google Scholar] | | Satinder Singh | University of Michigan | [Google Scholar] | | Mehdi Bennis | | [Google Scholar] | | David Silver | University College London / DeepMind | [Google Scholar] | | Rémi Munos | | [Google Scholar] | | Marc G. Bellemare | | [Google Scholar] | | Joelle Pineau | McGill University / Meta AI | [Google Scholar] | | Martin A. Riedmiller | Google | [Google Scholar] | | Mohsen Guizani | Mohamed Bin Zayed University of Artificial Intelligence