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Learning to reflect - data-driven strategies for stochastic control

Associate professor Claudia Strauch
Wednesday 24 November 2021 14:15–14:45 Aud. D2 (1531-119)
Inaugural lecture

One of the fundamental assumptions in stochastic control of continuous-time processes is that the dynamics of the underlying process are known. This is, however, usually obviously not fulfilled in practice. On the other hand, a rich theory for nonparametric estimation of the characteristics of continuous-time processes has been developed over the last years. We will discuss how to bring together these two areas for developing purely data-driven strategies for stochastic control, which we explore for ergodic singular control problems associated to continuous diffusions and Lévy processes.

Revised: 25.05.2023