Princeton Reinforcement Learning (RL) Lab

Welcome! The Princeton RL lab aims to develop effective and principled reinforcement learning algorithms. This includes studying/analyzing existing methods, building new methods, applying methods to new applications, and understanding what happens when you scale up these methods. Currently, there is a focus on understanding unsupervised/self-supervised methods, including methods that can propose their own goals and autonomously collect data.

Code for our projects is available at https://github.com/Princeton-RL.