Reinforcement learning is one of the most active research areas within machine learning. Recent empirical successes triggered a new wave of theoretical research in RL, with so many new directions opened in the past couple of years that it has become somewhat challenging to keep up with all the progress. This is made even worse in 2020 by the lack of in-person workshops and conferences.
This online seminar series aims to address these problems by providing a platform to get together and discuss the freshest work on RL theory. We aim to provide a balanced view of contemporary RL theory, and invite speakers covering a broad range of topics.