Skip to content
An introductory reinforcement learning course built on reveal.js
Branch: master
Clone or download
Pull request Compare This branch is 1 commit ahead, 1 commit behind hakimel:master.
Latest commit e879852 Apr 7, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
assets readme Apr 7, 2019
css 3.8.0 Apr 1, 2019
js 3.8.0 Apr 1, 2019
lib more forgiving code highlight line number format, add Promise polyfill Mar 14, 2019
plugin fix typos Apr 1, 2019
test add hasPlugin and getPlugin API methods and tests Apr 1, 2019
.gitignore fix npm security warnings, auto run tests when changed Apr 1, 2019
.travis.yml upgrade .travis nodejs version Feb 28, 2019
CONTRIBUTING.md note about plugins Mar 13, 2015
LICENSE 2019 Jan 10, 2019
README.md readme Apr 7, 2019
bower.json 3.8.0 Apr 1, 2019
demo.html better example for line range highlighting Apr 1, 2019
gruntfile.js fix grunt ci error Apr 1, 2019
index.html readme Apr 7, 2019
package-lock.json readme Apr 7, 2019
package.json readme Apr 7, 2019

README.md

Materials for the introductory reinforcement learning course A Glance at Reinforcement Learning. I also maintain a curated collection of reinforcement learning resources in the rl-resources repo.

This project is built and maintained by Adam Green - adam.green@adgefficiency.com.

Setup

brew install node 

npm install

npm start

Content

  • background statistical concepts
  • Markov Decision processes
  • value function methods (DQN and it's extensions)
  • policy gradient methods
  • AlphaGo to AlphaZero
  • practical advice for experiments
  • current state of the art

Goals for the course

Introduction to concepts, ideas and terminology. Familiarity with important literature. Understanding of the state of the field today. Practical strategies to run reinforcement learning experiments.

Where to go next

Further resources (video lectures, blog posts etc) are listed in dsr-rl/resources.md.

You can’t perform that action at this time.