van Dijk, Nico M.; Puterman, Martin L. Perturbation theory for Markov reward processes with applications to queueing systems. (English) Zbl 0642.60100 Adv. Appl. Probab. 20, No. 1, 79-98 (1988). Consider a discrete time, discrete state Markov chain where a bounded reward r(i) is obtained every time when the chain enters state i. The problem: If the transition probabilities and/or the reward function are perturbated to a certain amount, what will the change of the finite- horizon reward, the discounted infinite-horizon reward, the average reward and the total reward up to a random time be? Some easy to verify conditions are given which make the theorems concerned with the above questions better suited for applications e.g. in queueing theory. Reviewer: H.Daduna Cited in 1 ReviewCited in 22 Documents MSC: 60K30 Applications of queueing theory (congestion, allocation, storage, traffic, etc.) 90C47 Minimax problems in mathematical programming 90B22 Queues and service in operations research 90C31 Sensitivity, stability, parametric optimization Keywords:perturbation theory; Markov decision processes; reward function PDF BibTeX XML Cite \textit{N. M. van Dijk} and \textit{M. L. Puterman}, Adv. Appl. Probab. 20, No. 1, 79--98 (1988; Zbl 0642.60100) Full Text: DOI OpenURL