Implementation of Reinforcement Learning algorithms in Python, based on Sutton's & Barto's Book (Ed. 2)

Exercise Solutions for Reinforcement Learning: An Introduction [2nd Edition]

📖Learning reinforcement learning by implementing the algorithms from reinforcement learning an introduction

Jupyter notebook containing a solution to Sutton and Barto's gridworld problem with both a random agent and a Q-learning agent.

Implementation of various Reinforcement Learning Algorithms

Reinforcement Learning Introduction - Selected Exercise Solutions & Experiment Code

This is a Python implementation of concepts and algorithms described in "Reinforcement Learning: An Introduction" (Sutton and Barto, 2018, 2nd edition).

Q-Learing algorithm solves simple mazes.

Election results in the London Borough of Sutton.

Selected algorithms and exercises from the book Sutton, R. S. & Barton, A.: Reinforcement Learning: An Introduction. 2nd Edition, MIT Press, Cambridge, 2018.

Code for the reading group on Sutton & Barto: Reinforcement Learning

"Learning to Predict by the Methods of Temporal Differences" by Sutton, Richard S. (1988)

Reinforcement Learning

My solutions to Sutton and Barto's book 'Reinforcement Learning: An Introduction'

Reinforcement Learning Course from IPVS

Bandits in Numpy

Implementations of RL Algos and solved exercises for Sutton&Barto RLAI

Train an AI to drive on a simple racetrack, by using reinforcement learning with Q-Learning and Monte Carlo. Inspired by Sutton and Barto's book.