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
收藏
页码：2947 / 2958
页数：12
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