NECESSARY AND SUFFICIENT CONDITIONS FOR A BOUNDED SOLUTION TO THE OPTIMALITY EQUATION IN AVERAGE REWARD MARKOV DECISION CHAINS

被引：16

作者：

CAVAZOSCADENA, R ^{[1
]}

机构：

[1] UNIV AUTONOMA AGR ANTONIO NARRO,DEPT ESTADIST & CALCULO,SALTILLO,COAHUILA,MEXICO

来源：

SYSTEMS & CONTROL LETTERS | 1988年 / 10卷 / 01期

关键词：

MATHEMATICAL TECHNIQUES - State Space Methods - OPTIMIZATION;

D O I：

10.1016/0167-6911(88)90043-6

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 average reward Markov decision processes with discrete time parameter and denumerable state space. We are concerned with the following problem: find necessary and sufficient conditions so that, for arbitrary bounded reward function, the corresponding average reward optimality equation has a bounded solution. This problem is solved for a class of systems including the case in which, under the action of any stationary policy, the state space is an irreducible positive recurrent class.

引用

页码：71 / 78

页数：8