Before revision: This work studies the statistical limits of uniform convergence for offline policy evaluation (OPE) problems with model-based methods (for finite horizon MDP) and provides a unified view towards optimal learning for several well-motivated offline tasks.
After revision: This work studies the statistical limits of uniform convergence for offline policy evaluation (OPE) problems with model-based methods (for finite horizon MDP) and provides a unified framework towards optimal learning for several well-motivated offline tasks.