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UID:20261106T155747EST-7437UtXG1L@132.216.98.100
DTSTAMP:20261106T205747Z
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:https://www.mcgill.ca/cim/channels/event/submodular-mean-field-games-ex
 amples-general-formulation-351661
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