Risk-sensitive Markov decision problems under model uncertainty: finite time horizon case

Tomasz R. Bielecki; Tao Chen; Igor Cialenco

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arXiv · 2104.06915

Risk-sensitive Markov decision problems under model uncertainty: finite time horizon case

Tomasz R. Bielecki·Tao Chen·Igor Cialenco

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Abstract

In this paper we study a class of risk-sensitive Markovian control problems in discrete time subject to model uncertainty. We consider a risk-sensitive discounted cost criterion with finite time horizon. The used methodology is the one of adaptive robust control combined with machine learning.

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BibTeX RIS

Tomasz R. Bielecki, Tao Chen, Igor Cialenco. 2021-04-14. Risk-sensitive Markov decision problems under model uncertainty: finite time horizon case. https://arxiv.org/abs/2104.06915

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