Optimal threshold probability and expectation in semi-Markov decision processes

被引：10

作者：

Sakaguchi, Masahiko ^{[1
]}

Ohtsubo, Yoshio ^{[1
]}

机构：

[1] Kochi Univ, Fac Sci, Dept Math, Kochi 7808520, Japan

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2010年 / 216卷 / 10期

关键词：

Semi-Markov decision process; Optimal threshold probability; Existence of optimal policy; Value iteration; Policy improvement method; Stochastic order; MINIMIZING RISK MODELS;

D O I：

10.1016/j.amc.2010.04.007

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We consider undiscounted semi-Markov decision process with a target set and our main concern is a problem minimizing threshold probability. We formulate the problem as an infinite horizon case with a recurrent class. We show that an optimal value function is a unique solution to an optimality equation and there exists a stationary optimal policy. Also several value iteration methods and a policy improvement method are given in our model. Furthermore, we investigate a relationship between threshold probabilities and expectations for total rewards. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：2947 / 2958

页数：12

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