Unbounded cost Markov decision processes with limsup and liminf average criteria: new conditions

2005 ◽  
Vol 61 (3) ◽  
pp. 469-482 ◽  
Author(s):  
Quanxin Zhu ◽  
Xianping Guo ◽  
Yonglong Dai
Keyword(s):  
Markov Decision Processes ◽  
Decision Processes ◽  
Markov Decision ◽  
Unbounded Cost

scholarly journals Denumerable state continuous time Markov decision processes with unbounded cost and transition rates under average criterion

2002 ◽  
Vol 43 (4) ◽  
pp. 541-557 ◽  
Author(s):  
Xianping Guo ◽  
Weiping Zhu
Keyword(s):  
Markov Decision Processes ◽  
Continuous Time ◽  
Decision Processes ◽  
Transition Rates ◽  
Birth And Death Processes ◽  
Optimality Equation ◽  
Average Criterion ◽  
Markov Decision ◽  
Unbounded Cost ◽  
Queue Model

AbstractIn this paper, we consider denumerable state continuous time Markov decision processes with (possibly unbounded) transition and cost rates under average criterion. We present a set of conditions and prove the existence of both average cost optimal stationary policies and a solution of the average optimality equation under the conditions. The results in this paper are applied to an admission control queue model and controlled birth and death processes.

Extreme-point solutions in Markov decision processes

1983 ◽  
Vol 20 (04) ◽  
pp. 835-842
Author(s):  
David Assaf
Keyword(s):  
Convex Function ◽  
Extreme Point ◽  
Markov Decision Processes ◽  
Convex Functions ◽  
Sufficient Conditions ◽  
Decision Processes ◽  
Markov Decision ◽  
Full Solution

The paper presents sufficient conditions for certain functions to be convex. Functions of this type often appear in Markov decision processes, where their maximum is the solution of the problem. Since a convex function takes its maximum at an extreme point, the conditions may greatly simplify a problem. In some cases a full solution may be obtained after the reduction is made. Some illustrative examples are discussed.

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