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

arXiv: https://arxiv.org/abs/2104.06915 · HTML: https://mlsanity.com/paper/2104.06915/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2021.

## Built on by (most cited first, 1 of 1)

- [Distributional Method for Risk Averse Reinforcement Learning](https://mlsanity.com/paper/2302.14109/) (2023)

## Abstract (arXiv)

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.