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

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• 作者：Xiaolong Zou^a ; ^{sysuzxl@126.com" class="auth_mail" title="E-mail the corresponding author} ; Yonghui Huang^b ; ^{hyongh5@mail.sysu.edu.cn" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Continuous-time Markov decision processes ; Average reward criterion ; Unbounded transition rates ; Optimal stationary policy ; New optimality condition
• 刊名：Operations Research Letters
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：44
• 期：6
• 页码：742-746
• 全文大小：427 K

文摘

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.