Simulation-based optimization of Markov reward processes

被引：0

作者：

Marbach, P ^{[1
]}

Tsitsiklis, JN ^{[1
]}

机构：

[1] MIT, Informat & Decis Syst Lab, Cambridge, MA 02139 USA

来源：

PROCEEDINGS OF THE 37TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4 | 1998年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose a simulation-based algorithm for optimizing the average reward in a Markov Reward Process that depends on a set of parameters. As a special case, the method applies to Markov Decision Processes where optimization takes place within a parametrized set of policies. The algorithm involves the simulation of a single sample path, and can be implemented on-line. A convergence result (with probability 1) is provided.

引用

页码：2698 / 2703

页数：6

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