reinforcement-learning-resources
github.com/datascienceid/reinforcement-learning-resources ↗A curated list of awesome reinforcement courses, video lectures, books, library and many more.
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Curated Resources
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Free BooksCoursesVideos and LecturesPapersTutorialsSample CodeLibraries
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Courses
Free Books
- Algorithms for Reinforcement Learning by Csaba Szepesvari
- Artificial Intelligence: Foundations of Computational Agents by David Poole and Alan Mackworth
- Reinforcement Learning: An Introduction 1st Ed by Richard Sutton and Andrew Barto
- Reinforcement Learning: An Introduction 2nd Edition, in progress by Richard Sutton and Andrew Barto
Videos and Lectures
Papers
- Generalization in Reinforcement Learning: Successful examples using sparse coding, Richard S. Sutton
- Learning from Delayed Rewards, Cambridge, Chris Watkins
- Learning from Delayed Rewards, Christopher J. C. H. Watkins
- Learning to predict by the methods of temporal differences, Richard S. Sutton
- Monte Carlo Inversion and Reinforcement Learning, Andrew Barto, Michael Duff
- Reinforcement Learning with Replacing Eligibility Traces, Machine Learning, Satinder P. Singh, Richard S. Sutton
Tutorials
Showing a sample of 35 resources. View the full list on GitHub →