67 citations · 68 across the 5 of their papers we have counts for
5 papers · 1 filter
Risk-sensitive Markov decision problems under model uncertainty: finite time horizon case
Tomasz R. Bielecki, Tao Chen, Igor Cialenco
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 wi…
Nonparametric Adaptive Bayesian Stochastic Control Under Model Uncertainty
Tao Chen, Jiyoun Myung
In this paper we propose a new methodology for solving a discrete time stochastic Markovian control problem under model uncertainty. By utilizing the Dirichlet process, we model th…
Time-inconsistent Markovian control problems under model uncertainty with application to the mean-variance portfolio selection
Tomasz R. Bielecki, Tao Chen, Igor Cialenco
In this paper we study a class of time-inconsistent terminal Markovian control problems in discrete time subject to model uncertainty. We combine the concept of the sub-game perfec…
A Machine Learning Approach to Adaptive Robust Utility Maximization and Hedging
Tao Chen, Michael Ludkovski
We investigate the adaptive robust control framework for portfolio optimization and loss-based hedging under drift and volatility uncertainty. Adaptive robust problems offer many a…
Adaptive Robust Control Under Model Uncertainty
Tomasz R. Bielecki, Tao Chen, Igor Cialenco +2
In this paper we propose a new methodology for solving an uncertain stochastic Markovian control problem in discrete time. We call the proposed methodology the adaptive robust cont…