Risk-Averse Control of Undiscounted Transient Markov Models

Ozlem Cavus; Andrzej Ruszczynski

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arXiv · 1203.5437

Risk-Averse Control of Undiscounted Transient Markov Models

Ozlem Cavus·Andrzej Ruszczynski

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Abstract

We use Markov risk measures to formulate a risk-averse version of the undiscounted total cost problem for a transient controlled Markov process. We derive risk-averse dynamic programming equations and we show that a randomized policy may be strictly better than deterministic policies, when risk measures are employed. We illustrate the results on an optimal stopping problem and an organ transplant problem.

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BibTeX RIS

Ozlem Cavus, Andrzej Ruszczynski. 2014-03-22. Risk-Averse Control of Undiscounted Transient Markov Models. https://arxiv.org/abs/1203.5437

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