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20092025
most citedRisk-sensitive Markov control processes

78 citations · 667 across the 41 of their papers we have counts for

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6 papers · 1 filter

math.OC2023

Approximation of Optimal Feedback Controls for Stochastic Reaction-Diffusion Equations

Wilhelm Stannat, Alexander Vogler

In this paper we present a method to approximate optimal feedback controls for stochastic reaction-diffusion equations. We derive two approximation results providing the theoretica…

math.OC2023★ 3 cited

Neural Network Approximation of Optimal Controls for Stochastic Reaction-Diffusion Equations

Wilhelm Stannat, Alexander Vogler, Lukas Wessels

We present a numerical algorithm that allows the approximation of optimal controls for stochastic reaction-diffusion equations with additive noise by first reducing the problem to…

math.OC2020★ 28 cited

McKean-Vlasov SDEs in nonlinear filtering

Sahani Pathiraja, Sebastian Reich, Wilhelm Stannat

Various particle filters have been proposed over the last couple of decades with the common feature that the update step is governed by a type of control law. This feature makes th…

math.OC2019★ 5 cited

Deterministic Control of Stochastic Reaction-Diffusion Equations

Wilhelm Stannat, Lukas Wessels

We consider the control of semilinear stochastic partial differential equations (SPDEs) via deterministic controls. In the case of multiplicative noise, existence of optimal contro…

math.OC2014★ 1 cited

On Average Risk-sensitive Markov Control Processes

Yun Shen, Klaus Obermayer, Wilhelm Stannat

We introduce the Lyapunov approach to optimal control problems of average risk-sensitive Markov control processes with general risk maps. Motivated by applications in particular to…

math.OC2011★ 78 cited

Risk-sensitive Markov control processes

Yun Shen, Wilhelm Stannat, Klaus Obermayer

We introduce a general framework for measuring risk in the context of Markov control processes with risk maps on general Borel spaces that generalize known concepts of risk measure…