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Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.
| Date | Stars |
|---|---|
| 2026-07-31 | 868 |
| 2026-08-01 | 868 |
| 2026-08-02 | 868 |
| 2026-08-05 | 869 |
| 2026-08-06 | 869 |
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# David-Silver-Reinforcement-learning [](https://twitter.com/intent/tweet?text=David%20Silver%20Reinforcement%20Learning%20course%20notes%20along%20with%20implementation&url=https://github.com/dalmia/David-Silver-Reinforcement-learning&hashtags=deeplearning,reinforcementlearning,python,machinelearning,keras) []() [](https://travis-ci.org/athityakumar/colorls) [](http://makeapullrequest.com) This repository contains the notes for the Reinforcement Learning [course](www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html) by [David Silver](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Home.html) along with the implementation of the various algorithms discussed, both in Keras (with TensorFlow backend) and [OpenAI](https://openai.com/)'s [gym](https://github.com/openai/gym) framework. ## Syllabus: - Week 1: Introduction to Reinforcement Learning [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/intro_RL.pdf)][[video](https://www.youtube.com/watch?v=2pWv7GOvuf0&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=1)] - Week 2: Markov Decision Processes [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/MDP.pdf)][[video](https://www.youtube.com/watch?v=lfHX2hHRMVQ&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=2&t=3223s)] - Week 3: Planning by Dynamic Programming [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/DP.pdf)][[video](https://www.youtube.com/watch?v=Nd1-UUMVfz4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=3&t=417s)] - Week 4: Model-Free Prediction [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/MC-TD.pdf)][[video](https://www.youtube.com/watch?v=PnHCvfgC_ZA&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=4)] - Week 5: Model-Free Control [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/control.pdf)][[video](https://www.youtube.com/watch?v=0g4j2k_Ggc4&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=5)] - Week 6: Value Function Approximation [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/FA.pdf)][[video](https://www.youtube.com/watch?v=UoPei5o4fps&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=6)] - Week 7: Policy Gradient Methods [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/pg.pdf)][[video](https://www.youtube.com/watch?v=KHZVXao4qXs&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=7)] - Week 8: Integrating Learning and Planning [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/dyna.pdf)][[video](https://www.youtube.com/watch?v=ItMutbeOHtc&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=8)] - Week 9: Exploration and Exploitation [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/XX.pdf)][[video](https://www.youtube.com/watch?v=sGuiWX07sKw&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=9)] - Week 10: Case Study: RL in Classic Games [[slide](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching_files/games.pdf)][[video](https://www.youtube.com/watch?v=kZ_AUmFcZtk&list=PL7-jPKtc4r78-wCZcQn5IqyuWhBZ8fOxT&index=10)] ## Dependencies - TensorFlow - Keras - Gym - Numpy Install them using [pip](https://www.google.co.in/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjRhLWLnfHYAhVEtY8KHRqfCc4QFggoMAA&url=https%3A%2F%2Fpip.pypa.io%2Fen%2Fstable%2F&usg=AOvVaw18gydNGbBQg6WMxXoxO97K). ## Contributing Please feel free to create a Pull Request for adding implementations of the algorithms discussed in different frameworks like PyTorch, Caffe, etc. or improving the existing implementations. If you are a beginner, you can refer [this](https://opensource.guide/how-to-contribute/) for getting started. ## Support If you found this useful, please consider starring(★) the re
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matched fp:58ab5f58cb47803c, topic:reinforcement-learning, name:reinforcement learning, desc:reinforcement learning