Robustness of policies in constrained Markov decision processes

被引：15
|
作者：
Zadorojniy, A [1 ]
Shwartz, A
机构：
[1] Intel Israel Ltd, MATAM, IL-31015 Haifa, Israel
[2] Technion Israel Inst Technol, Fac Elect Engn, IL-32000 Haifa, Israel
来源：
IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2006年 / 51卷 / 04期
关键词：
constrained Markov decision process (MDP); discounted cost; Markov decision processes; robustness; sensitivity;
D O I：
10.1109/TAC.2006.872754
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 consider the optimization of finite-state, finite-action Markov decision processes (MDPs), under constraints. Cost and constraints are discounted. We introduce a new method for investigating the continuity, and a certain type of robustness, of the optimal cost and the optimal policy under changes in the constraints. This method is also applicable for other cost criteria such as finite horizon and infinite horizon average cost.
引用
收藏
页码：635 / 638
页数：4
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