Stochastic shortest path problems with associative accumulative criteria

被引：5

作者：

Ohtsubo, Yoshio ^{[1
]}

机构：

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

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2008年 / 198卷 / 01期

关键词：

shortest path problem; Markov decision process; associative criterion; invariant imbedding method; optimality equation; existence of optimal policy;

D O I：

10.1016/j.amc.2007.08.025

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We consider a stochastic shortest path problem with associative criteria in which for each node of a graph we choose a probability distribution over the set of successor nodes so as to reach a given target node optimally. We formulate such a problem as an associative Markov decision processes. We show that an optimal value function is a unique solution to an optimality equation and find an optimal stationary policy. Also we give a value iteration method and a policy improvement method. (C) 2007 Elsevier Inc. All rights reserved.

引用

页码：198 / 208

页数：11

共 20 条

[1]

[Anonymous], J FLUIDS ENG

[2]

BELLMAN RE, 1970, MANAGE SCI B-APPL, V17, pB141

[3] AN ANALYSIS OF STOCHASTIC SHORTEST-PATH PROBLEMS [J].