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SEMI-MARKOV DECISION PROCESSES

NONSTANDARD CRITERIA

Published online by Cambridge University Press:  22 October 2007

M. Baykal-Gürsoy  and
K. Gürsoy
M. Baykal-Gürsoy
Affiliation:
Department of Industrial and Systems EngineeringRutgers University, Piscataway, NJ E-mail: gursoy@rci.rutgers.edu
K. Gürsoy
Affiliation:
Department of Management ScienceKean UniversityUnion, NJ
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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.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 21 , Issue 4 , October 2007 , pp. 635 - 657
Copyright
Copyright © Cambridge University Press 2007

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