**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](https://github.com/Princeton-RL). # People ](assets/ben_eysenbach.png height=150) ](assets/chongyi_zheng.jpg height=150) ](assets/kathryn_wantlin.jpeg height=150) ](assets/michael_tang.jpg height=150) ](assets/raj_ghugare.jpeg height=150) ](assets/join_us.jpg height=150)