PyTorch implementations of algorithms from "Reinforcement Learning: An Introduction by Sutton and Barto", along with various RL research papers.
-
Updated
Aug 14, 2025 - Python
PyTorch implementations of algorithms from "Reinforcement Learning: An Introduction by Sutton and Barto", along with various RL research papers.
self-studying the Sutton & Barto the hard way
Python implementation of RL algorithms presented in Richard Sutton and Andrew Barto's book Reinforcement Learning: An Introduction (second edtion)
Classic RL control algorithm implementations found in Sutton and Barto book.
🧠 Implementation of various Reinforcement Learning algorithms.
Own implementation of the Q-learning algorithm presented on the example of the "treasure hunter" game.
Windy Grid World solution from sutton and bartos book.
This project implements a reinforcement learning solution for the classic Cart-Pole problem presented by Barto, Sutton, and Anderson, in which a pole is attached by an joint to a cart, which moves along a frictionless track. The pendulum starts upright and the goal is to balance the pole by applying forces in the left and right direction.
self-studying the Sutton & Barto the hard way
Add a description, image, and links to the sutton-barto-book topic page so that developers can more easily learn about it.
To associate your repository with the sutton-barto-book topic, visit your repo's landing page and select "manage topics."