Ranking and Selection as Stochastic Control
نویسندگان
چکیده
Under a Bayesian framework, we formulate the fully sequential sampling and selection decision in statistical ranking and selection as a stochastic control problem, and derive the associated Bellman equation. Using value function approximation, we derive an approximately optimal allocation policy. We show that this policy is not only computationally efficient but also possesses both one-step-ahead and asymptotic optimality for independent normal sampling distributions. Moreover, the proposed allocation policy is easily generalizable in the approximate dynamic programming paradigm.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1710.02619 شماره
صفحات -
تاریخ انتشار 2017