ShangtongZhang/reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
This project offers Python code examples that replicate the algorithms and figures from Sutton & Barto's 'Reinforcement Learning: An Introduction' textbook. It takes descriptions of various environments (like games or optimization problems) as input and produces outputs such as optimal policies, value functions, and learning curves, illustrating how different reinforcement learning methods perform. This resource is primarily for students, researchers, or practitioners learning or studying reinforcement learning concepts.
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Use this if you are studying the second edition of Sutton & Barto's 'Reinforcement Learning: An Introduction' and want to see practical, runnable code implementations of the concepts and algorithms presented in the book.
Not ideal if you are looking for a ready-to-use reinforcement learning library for building applications or solving new problems, as this is primarily an educational replication of textbook examples.
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Aug 09, 2024
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