Multilevel Simulation Based Policy Iteration for Optimal Stopping--Convergence and Complexity
نویسندگان
چکیده
منابع مشابه
Multilevel simulation based policy iteration for optimal stopping – convergence and complexity∗
This paper presents a novel approach to reduce the complexity of simulation based policy iteration methods for solving optimal stopping problems. Typically, Monte Carlo construction of an improved policy gives rise to a nested simulation algorithm. In this respect our new approach uses the multilevel idea in the context of the nested simulations, where each level corresponds to a specific numbe...
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Simulation-based policy iteration (SBPI) is a modification of the policy iteration algorithm for computing optimal policies for Markov decision processes. At each iteration, rather than solving the average evaluation equations, SBPI employs simulation to estimate a solution to these equations. For recurrent average-reward Markov decision processes with finite state and action spaces, we provide...
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ژورنال
عنوان ژورنال: SIAM/ASA Journal on Uncertainty Quantification
سال: 2015
ISSN: 2166-2525
DOI: 10.1137/140958463