Schedule

1. The Three Regimes of Offline-to-Online Reinforcement Learning - Lu Li, Tianwei Ni, Yihao Sun, Pierre-Luc Bacon

2. Task diversity produces systematic transfer but inhibits continual reinforcement learning - Purab Seth, Neil Shah, Kunal Jha, Samuel J. Gershman, Max Kleiman-Weiner, Wilka Carvalho

3. Flow-Corrected Thompson Sampling for Non-Stationary Contextual Bandits - AmirHossein Naghdi, Ali Baheri

4. Calibrated Partial Resets: Preventing Policy Collapse in Continual Reinforcement Learning - Luc McCutcheon, Evangelos Chatzaroulas, Saber Fallah

TL;DR: In this talk, I give a simple general definition of an agent, and ask: where in such an agent does learning take place? 

5. Forgetting is Everywhere - Ben Sanati, Thomas L Lee, Trevor McInroe, Aidan Scannell, Nikolay Malkin, David Abel, Amos Storkey

6. Security-Gym: Evaluating Temporally-Uniform Agents on High-Fidelity Linux Telemetry - Keith Lawson, Hafiz Malik

7. Connectivity, Credit Assignment, and the Speed of Learning - Edan Meyer, Andrew Freeman, Richard S Sutton

8. QD-Learning for Continual Reinforcement Learning - Zijing Wu, Doina Precup, Paul Masset, Nishanth Anand