IntroRL provides a framework for exploring Reinforcement Learning. It uses the text book "Reinforcement Learning" by Sutton & Barto as a reference.
This project is in the early stages of development.
IntroRL Provides A Framework For Exploring Reinforcement Learning.
It is based on the textbook “Reinforcement Learning An Introduction” By Sutton & Barto.
The textbook is also available in PDF format at the authors’ site.
This documentation of IntroRL is organized around the chapter structure of the Sutton & Barto textbook.
Many of the examples and figures are reproduced here in order to validate the IntroRL code.
There is another site by Shangtong Zhang that was of great help to me and which covers many areas of the textbook not covered here.
See the Code at: https://github.com/sonofeft/IntroRL
See the Docs at: http://introrl.readthedocs.org/en/latest/
See PyPI page at:https://pypi.python.org/pypi/introrl
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