BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20250723T091439EDT-6230xwOfUw@132.216.98.100 DTSTAMP:20250723T131439Z DESCRIPTION:\n \n \n ISS Informal Systems Seminar\n\n Speakers:\n\n \n Jodi Diane tti – Center for Mathematical Economics\, Bielefeld University\, Germany \n\n Max Nendel – Center for Mathematical Economics\, Bielefeld University\ , Germany \n \n\n  \n\n \n \n\n In the first part of the talk\, Jodi Dianetti presents some results on the existence and approximation of solutions for a class of mean field games with common noise and the related system of Mc Kean-Vlasov forward-backward stochastic differential equations. In particu lar\, some structural conditions are proposed\, which are related to the s ubmodularity of the underlying mean field game and are sort of an opposite version of the well known Lasry-Lions monotonicity condition. By reformul ating the representative player minimization problem via the stochastic ma ximum principle\, the submodularity conditions allow to prove comparison p rinciples for the forward-backward system\, which correspond to the monoto nicity of the best reply map. Building on this property\, existence and ap proximation of strong solutions is shown via Tarski's fixed point theorem. \n\n In the second part of the talk\, Max Nendel provides an abstract frame work for submodular mean field games and identifies verifiable sufficient conditions that allow to prove the existence and approximation of strong m ean field equilibria in models\, where data may not be continuous with res pect to the measure parameter and common noise is allowed. The setting is general enough to encompass qualitatively different problems\, such as mea n field games for discrete-time finite-space Markov chains\, singularly co ntrolled and reflected diffusions\, and mean field games of optimal timing . The analysis hinges on Tarski's fixed point theorem\, along with technic al results on lattices of flows of probability and sub-probability measure s.\n\n The talk is based on joint work with Giorgio Ferrari and Markus Fisc her.\n\n \n Biography: Short bio (Max Nendel): Max Nendel currently holds a position as an assistant professor for mathematical economics and finance at Bielefeld University. Moreover\, he is a principal investigator in the Bielefeld Collaborative Research Center 1283\, funded by the German Resear ch Foundation. He completed his Ph.D. in Mathematics in 2018 at the Univer sity of Konstanz under the joint supervision of Michael Kupper and Robert Denk. His scientific work focuses on mean field games as well as model unc ertainty in dynamical systems with applications in actuarial science and f inance. He mainly publishes in journals in the areas of pure and applied m athematics\, such as The Annals of Applied Probability\, Journal of Evolut ion Equations\, SIAM Journal on Control and Optimization\, Mathematical Fi nance\, and Insurance: Mathematics and Economics.\n\n Short bio (Jodi Diane tti): Jodi Dianetti is currently a postdoctoral researcher at Bielefeld Un iversity's Center for Mathematical Economics\, where he also obtained his Ph.D. in Mathematics in 2021 under the supervision of Giorgio Ferrari. Pri or to his Ph.D. studies\, he received his master degree in mathematics fro m the University of Padua in 2017. His research interests focus on stochas tic singular control problems\, stochastic differential games\, mean field games and their connections with PDE theory and stochastic analysis.\n \n \n \n\n DTSTART:20221007T143000Z DTEND:20221007T153000Z LOCATION:CA\, ZOOM SUMMARY:Submodular Mean Field Games: From Examples to a General Formulation URL:/cim/channels/event/submodular-mean-field-games-ex amples-general-formulation-351661 END:VEVENT END:VCALENDAR