Tutorial4RL

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

Related Repository

Repository	Remark
Awesome-Reinforcement-Learning-Papers
Tutorial4RL
2023-Reinforcement-Learning-Conferences-Papers
2022-Reinforcement-Learning-Conferences-Papers
2021-Reinforcement-Learning-Conferences-Papers
2020-Reinforcement-Learning-Conferences-Papers
2019-Reinforcement-Learning-Conferences-Papers
2018-Reinforcement-Learning-Conferences-Papers
2017-Reinforcement-Learning-Conferences-Papers

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	[Google Scholar]
Stefan Wermter	University of Hamburg	[Google Scholar]
Ying-Chang Liang		[Google Scholar]
Jonathan P. How		[Google Scholar]
Ivana Dusparic	Trinity College Dublin	[Google Scholar]
Robert Babuska	Delft University of Technology / Czech Technical University Prague	[Google Scholar]
Emma Brunskill	Stanford University	[Google Scholar]
Bo An	Nanyang Technological University	[Google Scholar]