Reinforcement Learning

Reinforcement Learning



This tutorial provides code, exercises and solutions for popular Reinforcement Learning algorithms. These are meant to serve as a learning tool to complement the theoretical materials from “Reinforcement Learning: An Introduction (2nd Edition)” and “David Silver’s Reinforcement Learning Course”.

Course Format: Online

Language: English

Eligibility: Public



Author:
Denny Britz

Source Repository:
https://github.com/dennybritz/reinforcement-learning

 

Description:

Overview

This repository provides code, exercises and solutions for popular Reinforcement Learning algorithms. These are meant to serve as a learning tool to complement the theoretical materials from

Each folder in corresponds to one or more chapters of the above textbook and/or course. In addition to exercises and solution, each folder also contains a list of learning goals, a brief concept summary, and links to the relevant readings.

All code is written in Python 3 and uses RL environments from OpenAI Gym. Advanced techniques use Tensorflow for neural network implementations.

Table of Contents

List of Implemented Algorithms

Resources

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