Explainable Reinforcement Learning via Model Transforms

1 code implementation • 24 Sep 2022 • Mira Finkelstein, Lucy Liu, Nitsan Levy Schlot, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenshein, Sarah Keren

This has given rise to a variety of approaches to explainability in RL that aim to reconcile discrepancies that may arise between the behavior of an agent and the behavior that is anticipated by an observer.

Decision Making reinforcement-learning +1