2023
Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces
AISTATS 2023poster
Principled decision-making in continuous state–action spaces is impossible without some assumptions. A common approach is to assume Lipschitz continuity of the Q-function. We show that, unfortunately, this property fails to hold in many typical domains. We propose a new coarse-grained smoothness def…