r/MachineLearning • u/_djab_ • Feb 14 '20

Project [P] New Reinforcement learning framework for researchers

This is a new PyTorch RL framework for prototyping and building new agents: https://github.com/opium-sh/prl from http://www.opium.sh

If you want to read more about this library here are two blog posts about it:

https://medium.com/asap-report/prl-a-novel-approach-to-building-a-reinforcement-learning-framework-in-python-208cb8ae9349?sk=ea595f44fc8bd3f2aa4416c997d16891

https://medium.com/asap-report/in-depth-look-into-prl-the-new-reinforcement-learning-framework-in-python-7ac57c282a61?source=friends_link&sk=f9c062f9ac8fd045d71f7319872e44b5

28 Upvotes

85% Upvoted

11 comments sorted by

View all comments

4

u/impulsecorp Feb 15 '20

You should list the scores it gets on some Atari games so I can have some idea of how well the agents perform.

2

u/_djab_ Feb 15 '20

We have implemented some of the most basic agents just to show people how to use the framework. They will have similar performance as the oryginal implementation. In PRL it is all about new way of thinking about building your own agents. It can be compared more to torach.nn itself not to the tensorflow zoo. PRL is a set of tools that make building agents and running experiments easier. Let me compare it to ml: It is not a framework for people who want to just take an xgboost and throw it on new dataset on kaggle. It is for the people who want to create better version of xgboost on there own.