Seminari Filippo De Feo e Mattia Martini - Politecnico di Milano - 8 Gennaio 2026
Si ricordano i seguenti 2 seminari a tutti gli interessati. SEMINARIO 1: Giovedì 8 Gennaio 2026, ore 11:00. Aula Seminari III Piano, Dipartimento di Matematica, Politecnico di Milano. Speaker: Filippo De Feo, Technische Universität Berlin. Title: Stochastic Optimal Control of Interacting Particle Systems in Hilbert Spaces and Applications in Economics. Abstract: Optimal control of interacting particles governed by stochastic evolution equations in Hilbert spaces is an open area of research. Such systems naturally arise in formulations where each particle is modeled by stochastic partial differential equations, path-dependent stochastic differential equations (such as stochastic delay differential equations or stochastic Volterra integral equations), or partially observed stochastic systems. In this talk we present a limiting theory as the number of particles tends to infinity. We apply the developed theory to problems arising in economics where the particles are modeled by stochastic partial differential equations and stochastic delay differential equations. The talks is based on [F. de Feo, F. Gozzi, A. Swiech, L. Wessels, Stochastic Optimal Control of Interacting Particle Systems in Hilbert Spaces and Applications, arXiv preprint arXiv:2511.21646] Link Zoom: https://polimi-it.zoom.us/j/92373976166?pwd=pvQAMGRkAnZ6WLaEXawDkGmbxa61VV.1 Link Seminario Polimi: https://www.mate.polimi.it/eventi/?id=2663&sezione_di_ricerca=probstat&stringa=&submit=Submit#single SEMINARIO 2: Giovedì 8 Gennaio 2026, ore 11:45. Aula Seminari III Piano, Dipartimento di Matematica, Politecnico di Milano. Speaker: Mattia Martini, École polytechnique, Centre de Mathématiques Appliquées, Palaiseau. Title: Regularisation in mean field models via infinite dimensional diffusion. Abstract: This talk aims to show how randomizing the dynamics in mean field models can help regularize the associated partial differential equations on the space of probability measures. A key challenge in this approach lies in constructing a suitable notion of noise on the space of probability measures. To this end, we rely on the Dirichlet–Ferguson diffusion process, as studied by Dello Schiavo [AOP 22]. We first examine the effect of this noise on a system of uncontrolled interacting particles and show that it induces a regularizing effect at the level of the corresponding backward Kolmogorov equation. We then analyze a mean field control problem driven by this noise and prove that the associated Hamilton–Jacobi equation admits a unique solution in an appropriate functional space, even when the coefficients have limited regularity. The talk is based on a joint work with F. Delarue (Nice) and G. Sodini (Vienna). Link Zoom: https://polimi-it.zoom.us/j/92373976166?pwd=pvQAMGRkAnZ6WLaEXawDkGmbxa61VV.1 Link Seminario Polimi: https://www.mate.polimi.it/eventi/?id=2664&sezione_di_ricerca=probstat&stringa=&submit=Submit#single ----- Prof. Luca Scarpa, PhD Associate Professor in Probability Department of Mathematics Politecnico di Milano Via E. Bonardi 9 20133 Milano, Italy e.mail: luca.scarpa@polimi.it<mailto:luca.scarpa@polimi.it> url: https://sites.google.com/view/lucascarpa
participants (1)
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Luca Scarpa