This is a brief guide for deep reinforcement learning projects in MSAIL 2020-2021.
We'll be using OpenAI's Gym environment for this project.
- OpenAI Gym - The Gym main website
- OpenAI Gym Github Repo - The Raw code of Gym in Github
- OpenAI Gym Documentation - Documentation, with installation instruction
- Deeplizard RL Module - some combination of theory and OpenAI Gym
- Deep Reinforcement Learning Series (Jonathan Hui) - A deep RL series on Medium that covers a lot of important topics (DQNs, Policy Gradients, etc)
- Deep RL Course - A series with a more implementation heavy approach: they teach Deep RL concepts through implementing agents for different games (Space Invaders, Doom, Sonic)
More Resources: All of these Github repos have links to a ton of useful RL content (other tutorials, courses, textbooks, blog posts, research papers, etc)
Thanks to Qianbo Yin (Grayson) for compiling the first iteration of this resource guide
Michigan Student Artificial Intelligence Lab (MSAIL) 2020-2021