The paper derives a bridge-function identification result that supports root-n-rate policy value estimation and policy-gradient policy learning for continuous actions under unmeasured confounding.
(2008), Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path, Machine Learning, 71, 89--129
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Reinforcement Learning with Continuous Actions Under Unmeasured Confounding
The paper derives a bridge-function identification result that supports root-n-rate policy value estimation and policy-gradient policy learning for continuous actions under unmeasured confounding.