The Variance of Discounted Rewards in Markov Decision Processes: Laurent Expansion and Sensitive Optimality

被引：0
|
作者：
Sladky, Karel [1 ]
机构：
[1] AS CR, Inst Informat Theory & Automat, Dept Econometr, Prague 8, Czech Republic
来源：
MATHEMATICAL METHODS IN ECONOMICS (MME 2014) | 2014年
关键词：
discrete-time Markov decision chains; variance of total discounted rewards; Laurent expansion; mean-variance optimality;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In this paper we consider discounted Markov decision processes with finite state space and compact actions spaces. We present formulas for the variance of total expected discounted rewards along with its partial Laurent expansion. This enables to compare the obtained results with similar results for undiscounted models.
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页码：908 / 913
页数：6
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