Mean-variance criteria in an undiscounted Markov decision process

Mean-variance criteria in an undiscounted Markov decision process

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Article ID: iaor1997338
Country: Netherlands
Volume: 69
Issue: 2
Start Page Number: 265
End Page Number: 276
Publication Date: Sep 1993
Journal: European Journal of Operational Research
Authors:
Abstract:

In the steady state of an undiscounted Markov decision process, the paper considers the problem of finding an optimal stationary probability distribution that minimizes the variance of the reward in a transition among the stationary probability distributions which give a mean not less than a specified value. The problem consists of a mathematical program with linear constraints and a non-linear objective. The solution technique replaces the non-linear part of the objective with a constant, inserts the constant as a constraint, and then parametrically analyzes the resulting linear program. Three numerical examples are discussed.

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