A python implementation of the concepts in the book "Reinforcement Learning: An Introduction" by R.S. Sutton and A. G. Barto.
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Updated
Jul 13, 2020 - Jupyter Notebook
A python implementation of the concepts in the book "Reinforcement Learning: An Introduction" by R.S. Sutton and A. G. Barto.
⚡️ Code and Notes 📝 for Grokking Deep RL and RL: An Introduction by Sutton & Barto(2nd edition, 2018) 🤘
Some python implementations from the book, "Reinforcement Learning: An Introduction" by Andrew Barto and Richard S. Sutton.
My own codes for exercises of the book by Sutton and Barto
Python implementation of RL algorithms presented in Richard Sutton and Andrew Barto's book Reinforcement Learning: An Introduction (second edtion)
Cheatsheet of Reinforcement Learning (Based on Sutton-Barto Book - 2nd Edition)
This repo consists of all the Python notebooks that are part of the Coursera specialization for Reinforcement Learning.
Not A Replication of Sutton
Implementations of RL Algos and solved exercises for Sutton&Barto RLAI
self-studying the Sutton & Barto the hard way
self-studying the Sutton & Barto the hard way
simple cliff walk implementation
My take on some problems from "Reinforcement Learning: An Introduction" by Sutton & Barto
A summary of important concepts and algorithms in RL
Recreation of the classic video-game "The Snake" into a 3D scenario. Implemented with Monte Carlo ES algorithm.
Own implementation of the Q-learning algorithm presented on the example of the "treasure hunter" game.
🧠 Implementation of various Reinforcement Learning algorithms.
Classic RL control algorithm implementations found in Sutton and Barto book.
implementations of RL algorithms from Sutton's textbook and various papers
reinforcement learning algorithms, models and experiments
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