min

Recall thatx = argmina Ax>θ so x can be viewed as a deterministic functionθ . " log p(zn|θ) (1/|Nε|) P Since Rmax is the upper bound of maximum expected reward, the second term can be bounded 2Rmaxγ. We letΦ R|A| d as the feature matrix where each row ofΦrepresent each action inA. We summarize the procedure of estimating t,It inAlgorithm3. LetX denote the feasible set.