Semi-Markov decision processes: Nonstandard criteria

Document Type

Article

Publication Date

1-1-2007

Abstract

Considered are semi-Markov decision processes (SMDPs) with finite state and action spaces. We study two criteria: the expected average reward per unit time subject to a sample path constraint on the average cost per unit time and the expected time-average variability. Under a certain condition, for communicating SMDPs, we construct (randomized) stationary policies that are ε-optimal for each criterion; the policy is optimal for the first criterion under the unichain assumption and the policy is optimal and pure for a specific variability function in the second criterion. For general multichain SMDPs, by using a state space decomposition approach, similar results are obtained. © 2007 Cambridge University Press.

Publication Title

Probability in the Engineering and Informational Sciences

First Page Number

635

Last Page Number

657

DOI

10.1017/S026996480700037X

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