48 citations · 357 across the 28 of their papers we have counts for
7 papers · 1 filter
Continuous-time mean field Markov decision models
Nicole Bäuerle, Sebastian Höfer
We consider a finite number of statistically equal agents, each moving on a finite set of states according to a continuous-time Markov Decision Process (MDP). Transition intens…
Risk-Sensitive Stopping Problems for Continuous-Time Markov Chains
Nicole Bäuerle, Anton Popp
In this paper we consider stopping problems for continuous-time Markov chains under a general risk-sensitive optimization criterion for problems with finite and infinite time horiz…
Optimal Dividend Payout Model with Risk Sensitive Preferences
Nicole Bäuerle, Anna Jaśkiewicz
We consider a discrete-time dividend payout problem with risk sensitive shareholders. It is assumed that they are equipped with a risk aversion coefficient and construct their disc…
Partially Observable Risk-Sensitive Markov Decision Processes
Nicole Bäuerle, Ulrich Rieder
We consider the problem of minimizing a certainty equivalent of the total or discounted cost over a finite and an infinite time horizon which is generated by a Partially Observable…
Exact and Approximate Hidden Markov Chain Filters Based on Discrete Observations
Nicole Bäuerle, Igor Gilitschenski, Uwe D. Hanebeck
We consider a Hidden Markov Model (HMM) where the integrated continuous-time Markov chain can be observed at discrete time points perturbed by a Brownian motion. The aim is to deri…
Risk-Sensitive Dividend Problems
Nicole Bäuerle, Anna Jaśkiewicz
We consider a discrete-time version of the popular optimal dividend pay-out problem in risk theory. The novel aspect of our approach is that we allow for a risk averse insurer, i.e…
A Note on Applications of Stochastic Ordering to Control Problems in Insurance and Finance
Nicole Bauerle, Erhan Bayraktar
We consider a controlled diffusion process where the controller is allowed to choose the drift and the volatility from a set $\K(x) \subset \R\times (0…