Reinforcement Learning
post by ISH GIRWAN

Courses/Tutorials

• Deep Reinforcement Learning, Spring 2017, by UC Berkeley: http://rll.berkeley.edu/deeprlcours...
• Reinforcement Learning, 2015, by UCL (David Siver): http://www0.cs.ucl.ac.uk/staff/d.si...
• https://github.com/yandexdataschool...
• Lecture notes by Andrew Ng: http://cs229.stanford.edu/notes/cs2...
• https://medium.com/emergent-future/...

Books

• Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto: http://webdocs.cs.ualberta.ca/~sutt...

Blogs

• http://bair.berkeley.edu/blog

I think you can take the UC Berkeley course instead of David Silver's course as it's more up to date. Additionally you can check Arthur Juliani's blog series, it's really good.

相关课程

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微积分, coursera, 吉姆·福勒
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以下是比较旧的RL Course by David Silver

UCL Course on RL
http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html

Advanced Topics  2015 (COMPM050/COMPGI13)

Reinforcement Learning

Contact: d.silver@cs.ucl.ac.uk

Video-lectures available here

Lecture 1: Introduction to Reinforcement Learning

Lecture 2: Markov Decision Processes

Lecture 3: Planning by Dynamic Programming

Lecture 4: Model-Free Prediction

Lecture 5: Model-Free Control

Lecture 6: Value Function Approximation

Lecture 7: Policy Gradient Methods

Lecture 8: Integrating Learning and Planning

Lecture 9: Exploration and Exploitation

Lecture 10: Case Study: RL in Classic Games

Easy21 assignment

Discussion and announcements: http://groups.google.com/group/csml-advanced-topics

Previous RL exam questions and answers