Bing-Yi Jing

Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning

This paper proposes a model-based bootstrap framework for uncertainty quantification of OPE in finite-horizon, time-inhomogeneous Markov decision processes (MDPs), and establishes bootstrap distributional consistency, asymptotically valid confidence intervals, and consistent variance estimation for the target policy va...