Optimal Value Inference for Reinforcement Learning
Two new nuisances are derived as fixed points of a self-induced Bellman equation, in which they approximate the maximum Bellman operator by its softmax correspondence, and a debiased estimator is proposed through the Neyman orthogonality and established its asymptotic normality under diverging horizons.
Nan Lu, Ethan Lee, James M. Robins et al.
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