Implementations of RL Algos and solved exercises for Sutton&Barto RLAI
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Updated
Aug 31, 2021 - Jupyter Notebook
Implementations of RL Algos and solved exercises for Sutton&Barto RLAI
🧠 Implementation of various Reinforcement Learning algorithms.
This repo consists of all the Python notebooks that are part of the Coursera specialization for Reinforcement Learning.
My own codes for exercises of the book by Sutton and Barto
Classic RL control algorithm implementations found in Sutton and Barto book.
Some python implementations from the book, "Reinforcement Learning: An Introduction" by Andrew Barto and Richard S. Sutton.
Own implementation of the Q-learning algorithm presented on the example of the "treasure hunter" game.
My take on some problems from "Reinforcement Learning: An Introduction" by Sutton & Barto
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.
self-studying the Sutton & Barto the hard way
Recreation of the classic video-game "The Snake" into a 3D scenario. Implemented with Monte Carlo ES algorithm.
Not A Replication of Sutton
implementations of RL algorithms from Sutton's textbook and various papers
simple cliff walk implementation
reinforcement learning algorithms, models and experiments
Reinforcement Learning Algorithms in a simple Gridworld
Python implementation of RL algorithms presented in Richard Sutton and Andrew Barto's book Reinforcement Learning: An Introduction (second edtion)
A summary of important concepts and algorithms in RL
Reinforcement Learning (Sutton, Barto) - solved exercises
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