Skip to content

A collection of Reinforcement Learning GitHub code resources divided by frameworks and environments

Notifications You must be signed in to change notification settings

TheMTank/RL-code-resources

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 

Repository files navigation

RL-code-resources

A collection of Reinforcement Learning code resources, frameworks and environments. Every link below is a GitHub link so this is mainly focused on resources that are directly related to open-source code. For other types of resources check out awesome-rl, spinning up and our 4 hour Reinforcement Learning course we created: An Introduction to Deep Reinforcement Learning

Feel free to raise issues, pull requests or email us at [email protected] for missing resources you think we should add.

RL Frameworks and design patterns

There really aren't many truly popular RL "frameworks" (i.e. the equivalent of DL frameworks but for RL) and there isn't even agreed upon formal design patterns/workflows that are common across all RL algorithm implementations. Also, the distinction between framework and "collection of algorithms" is hard to specify sometimes. Therefore, the below list is a mix within this continuum as well as some RL courses.

PyTorch

TensorFlow

Other

RL Environments

General collections

3D Environments

https://github.com/allenai/ai2thor

Real Time Strategy (RTS)

https://github.com/deepmind/pysc2

Control and robotics

Some of these aren't necessarily for RL but could be for motion planning and simulating complex robotics systems.

Multi-agent

GridWorlds

Non-RL based (e.g. vision)

Other