The expected total cost criterion for Markov decision processes under constraints (Q2856038)
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scientific article; zbMATH DE number 6218390
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | The expected total cost criterion for Markov decision processes under constraints |
scientific article; zbMATH DE number 6218390 |
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23 October 2013
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Markov decision process
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expected total cost criterion
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linear programming
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occupation measure
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0.9761856
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0.9381834
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0.9279606
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0.91904616
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0.91741824
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The expected total cost criterion for Markov decision processes under constraints (English)
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Discrete-time Markov processes (MDPs) with constraints and objectives of the form of expected total cost over the infinite horizon are studied. The problem is analyzed using the linear programming approach. It is shown that if there exists an optimal solution for the associated linear program then there exists a randomized stationary policy which is optimal for the MDP and the optimal value for both problems coincides. Also it is proved that the set of randomized stationary policies provides a sufficient set for solving the MDP. The authors do not assume that the MDP is transient or absorbing and the cost function is nonnegative or bounded below. Three examples that illustrate the obtained results are given.
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