Verifiable conditions for average optimality of continuous-time Markov decision processes

被引：0

作者：

Zou, Xiaolong ^{[1
]}

Huang, Yonghui ^{[2
]}

机构：

[1] Guangzhou Univ, Sch Econ & Stat, Guangzhou 510006, Guangdong, Peoples R China

[2] Sun Yat Sen Univ, Sch Math, Guangzhou 510275, Guangdong, Peoples R China

来源：

OPERATIONS RESEARCH LETTERS | 2016年 / 44卷 / 06期

关键词：

Continuous-time Markov decision processes; Average reward criterion; Unbounded transition rates; Optimal stationary policy; New optimality condition;

D O I：

10.1016/j.orl.2016.09.007

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

In this paper we provide another set of verifiable conditions for the average optimality of continuous time Markov decision processes (CTMDP) in Polish spaces with unbounded transition rates. Under the new conditions which are imposed on the primitive data of the model of the CTMDP and thus easy to verify, we also establish the existence of an average optimal stationary policy. Finally, we propose two examples to illustrate the newness of the conditions. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：742 / 746

页数：5

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