Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Reinforcement learning resources curated
| Date | Stars |
|---|---|
| 2026-08-05 | 9902 |
| 2026-08-06 | 9905 |
| 2026-08-07 | 9906 |
| 2026-08-09 | 9908 |
| 2026-08-10 | 9909 |
| 2026-08-11 | 9910 |
| 2026-08-13 | 9913 |
| 2026-08-14 | 9914 |
| 2026-08-15 | 9915 |
| 2026-08-18 | 9914 |
| 2026-08-19 | 9915 |
| 2026-08-20 | 9915 |
| 2026-08-21 | 9917 |
| 2026-08-22 | 9918 |
| 2026-08-23 | 9917 |
| 2026-08-24 | 9918 |
| 2026-08-25 | 9919 |
| 2026-08-26 | 9920 |
| 2026-08-27 | 9922 |
| 2026-08-29 | 9926 |
| 2026-08-30 | 9928 |
| 2026-08-31 | 9931 |
| 2026-09-01 | 9935 |
| 2026-09-02 | 9937 |
| 2026-09-03 | 9938 |
| 2026-09-04 | 9937 |
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| 2026-09-06 | 9937 |
| 2026-09-07 | 9938 |
| 2026-09-08 | 9937 |
| 2026-09-10 | 9940 |
| 2026-09-11 | 9947 |
| 2026-09-12 | 9949 |
| 2026-09-13 | 9953 |
| 2026-09-14 | 9957 |
| 2026-09-15 | 9959 |
| 2026-09-16 | 9960 |
| 2026-09-17 | 9964 |
| 2026-09-18 | 9967 |
| 2026-09-19 | 9968 |
| 2026-09-20 | 9971 |
| 2026-09-21 | 9977 |
| 2026-09-22 | 9980 |
| 2026-09-23 | 9980 |
| 2026-09-24 | 9982 |
| 2026-09-25 | 9980 |
| 2026-09-26 | 9982 |
| 2026-09-27 | 9985 |
| 2026-09-28 | 9990 |
| 2026-09-29 | 9991 |
| 2026-09-30 | 9994 |
| 2026-10-01 | 9997 |
| 2026-10-02 | 10000 |
| 2026-10-03 | 10001 |
| 2026-10-04 | 10003 |
| 2026-10-05 | 10002 |
| 2026-10-06 | 10006 |
| 2026-10-07 | 10008 |
| 2026-10-08 | 10010 |
| 2026-10-09 | 10011 |
| 2026-10-10 | 10010 |
| 2026-10-11 | 10012 |
| 2026-10-13 | 10013 |
| 2026-10-15 | 10014 |
| 2026-10-16 | 10015 |
| 2026-10-18 | 10014 |
| 2026-10-19 | 10017 |
| 2026-10-20 | 10021 |
| 2026-10-21 | 10022 |
| 2026-10-22 | 10023 |
| 2026-10-23 | 10024 |
| 2026-10-25 | 10025 |
| 2026-10-26 | 10026 |
| 2026-10-27 | 10025 |
| 2026-10-28 | 10024 |
| 2026-10-29 | 10029 |
| 2026-10-31 | 10029 |
| 2026-11-01 | 10030 |
| 2026-11-03 | 10030 |
| 2026-11-04 | 10030 |
Today
— stars today
This week
+6 stars this week
This month
+28 stars this month
Momentum
0.0
growth rate 0.06%/day
# Awesome Reinforcement Learning [](https://github.com/sindresorhus/awesome)
This page is no longer maintained.
A curated list of resources dedicated to reinforcement learning.
We have pages for other topics: [awesome-rnn](https://github.com/kjw0612/awesome-rnn), [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision), [awesome-random-forest](https://github.com/kjw0612/awesome-random-forest)
Maintainers: [Hyunsoo Kim](http://sites.duke.edu/hyunsookim/), [Jiwon Kim](http://github.com/kjw0612)
## Contributing
Please feel free to [pull requests](https://github.com/aikorea/awesome-rl/pulls)
## Table of Contents
- [Theory](#theory)
- [Lectures](#lectures)
- [Books](#books)
- [Surveys](#surveys)
- [Papers / Thesis](#papers--thesis)
- [Applications](#applications)
- [Game Playing](#game-playing)
- [Robotics](#robotics)
- [Control](#control)
- [Operations Research](#operations-research)
- [Human Computer Interaction](#human-computer-interaction)
- [Codes](#codes)
- [Tutorials / Websites](#tutorials--websites)
- [Online Demos](#online-demos)
- [Open Source Reinforcement Learning Platforms](#open-source-reinforcement-learning-platforms)
## Codes
- Codes for examples and exercises in Richard Sutton and Andrew Barto's Reinforcement Learning: An Introduction
- [Python Code](https://github.com/ShangtongZhang/reinforcement-learning-an-introduction)
- [MATLAB Code (BROKEN LINK)](http://waxworksmath.com/Authors/N_Z/Sutton/sutton.html)
- [C/Lisp Code](http://incompleteideas.net/book/code/code2nd.html)
- [Julia Code](https://github.com/Ju-jl/ReinforcementLearningAnIntroduction.jl)
- [Book](http://incompleteideas.net/book/RLbook2018.pdf)
- [Exercise Solutions](https://github.com/LyWangPX/Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions)
- Simulation code for Reinforcement Learning Control Problems
- [Pole-Cart Problem](http://pages.cs.wisc.edu/~finton/poledriver.html)
- [Q-learning Controller](http://pages.cs.wisc.edu/~finton/qcontroller.html)
- [MATLAB Environment and GUI for Reinforcement Learning](http://www.cs.colostate.edu/~anderson/res/rl/matlabpaper/rl.html)
- [Reinforcement Learning Repository - University of Massachusetts, Amherst](http://www-anw.cs.umass.edu/rlr/)
- [Brown-UMBC Reinforcement Learning and Planning Library (Java)](http://burlap.cs.brown.edu/)
- [Reinforcement Learning in R (MDP, Value Iteration)](http://www.moneyscience.com/pg/blog/StatAlgo/read/635759/reinforcement-learning-in-r-markov-decision-process-mdp-and-value-iteration)
- [Reinforcement Learning Environment in Python and MATLAB](https://jamh-web.appspot.com/download.htm)
- [RL-Glue](http://glue.rl-community.org/wiki/Main_Page) (standard interface for RL) and [RL-Glue Library](http://library.rl-community.org/wiki/Main_Page)
- [PyBrain Library](http://www.pybrain.org/) - Python-Based Reinforcement learning, Artificial intelligence, and Neural network
- [RLPy Framework](http://rlpy.readthedocs.org/en/latest/) - Value-Function-Based Reinforcement Learning Framework for Education and Research
- [Maja](http://mmlf.sourceforge.net/) - Machine learning framework for problems in Reinforcement Learning in python
- [TeachingBox](http://servicerobotik.hs-weingarten.de/en/teachingbox.php) - Java based Reinforcement Learning framework
- [Policy Gradient Reinforcement Learning Toolbox for MATLAB](http://www.ias.informatik.tu-darmstadt.de/Research/PolicyGradientToolbox)
- [PIQLE](http://sourceforge.net/projects/piqle/) - Platform Implementing Q-Learning and other RL algorithms
- [BeliefBox](https://code.google.com/p/beliefbox/) - Bayesian reinforcement learning library and toolkit
- [Deep Q-Learning with TensorFlow](https://github.com/nivwusquorum/tensorflow-deepq) - A deep Q learning demonstration using Google Tensorflow
- [Atari](https://github.comExcerpt of 35,741 characters
Read on GitHub
98
Jiwon Kim · SK Telecom
21
wassname (Michael J Clark) · I'm just a guy who likes to machine learn · Australia
7
4
3
2
Keng · United States
2
justheuristic · YSDA
2
Mithi Sevilla · Singapore
2
Ken Fehling
2
2
Shangtong Zhang · University of Virginia · United States
2
United Kingdom
2
2
Andrew · University of Toronto · Canada
2
nikr
2
Vadim Borisov
2
1
Thomas Simonini · @huggingface · France
1
Megvii Research · China
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:d84f127b49e53d54, desc:reinforcement learning