Atelier: Jeux à champ moyen11 au 15 avril 2022Programme |
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Le lundi 11 avril 2022 |
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Salle(s) de réunion : 6214/6254 |
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09:20 - 09:30
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Mot de bienvenue
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09:30 - 10:30
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Peter Edwin Caines
(McGill University) Vertexon-Graphons and Embedded GMFG Systems | Résumé |
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10:30 - 11:00
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Pause-café
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Salle(s) 6245
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11:00 - 12:00
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Daniel Lacker
(Columbia University) A case study on stochastic games on large graphs in mean field and sparse regimes | Résumé
Présentation |
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12:00 - 14:00
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Déjeuner
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14:00 - 15:00
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Asaf Cohen
(University of Michigan) Markovian Equilibria In Ergodic Many-Player Games and Mean-Field Games | Résumé
Présentation |
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15:00 - 16:00
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Charles Bertucci
(École Polytechnique - CNRS) Monotone solutions for the mean field games master equations | Résumé |
Le mardi 12 avril 2022 |
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Salle(s) de réunion : 6214/6254 |
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09:00 - 10:00
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Pierre-Louis Lions
(Collège de France) Complete" Analysis of the Master Equation: an Example | Présentation |
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10:00 - 10:10
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Sarah Perrin
(Univ. Lille / Inria Scool) Generalization in Mean Field Games by Learning Master Policies | Résumé |
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10:10 - 10:20
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Zachary Bezemek
(Boston University) Moderate deviations for fully coupled multiscale weakly interacting particle systems | Résumé
Présentation |
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10:20 - 10:30
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Lane Chun Yeung
(Columbia University) A non-asymptotic perspective on mean field control | Résumé
Présentation |
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10:30 - 11:00
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Pause-café
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Salle(s) 6245
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11:00 - 12:00
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Daniela Tonon
(Università di Padova) A comparison principle for Hamilton-Jacobi equations on infinite dimensional spaces | Résumé
Présentation |
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12:00 - 14:00
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Déjeuner
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14:00 - 15:00
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Pierre Cardaliaguet
(Université Paris-Dauphine) PDE approaches to mean field games with a common noise | Résumé |
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15:00 - 16:00
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Rene Carmona
(Princeton U.) Model-Free Mean-Field Reinforcement Learning: Mean-Field MDP and Mean-Field Q-Learning | Résumé |
Le mercredi 13 avril 2022 |
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Salle(s) de réunion : 6214/6254 |
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09:00 - 10:00
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Mathieu Laurière
(NYU Shanghai) On machine learning methods for mean field master equations | Résumé |
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10:00 - 10:10
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Joe Jackson
(The University of Texas at Austin) An algebraic rate for the convergence problem in mean field control | Résumé
Présentation |
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10:10 - 10:20
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Jiacheng Zhang
(UC berkeley) A mean field framework for the Stackelberg game: algorithms and sensitivity analysis | Résumé
Présentation |
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10:30 - 11:00
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Pause-café
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Salle(s) 6245
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11:00 - 12:00
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François Delarue
(Université Nice-Sophia Antipolis) Common noise via rearranged stochastic heat equation | Résumé
Présentation |
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12:00 - 14:00
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Déjeuner
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14:00 - 15:00
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Minyi Huang
(Carleton University ) Mean field Stackelberg games and time consistent strategies | Résumé
Présentation |
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15:00 - 15:45
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Session ouverte de problème
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Le jeudi 14 avril 2022 |
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Salle(s) de réunion : 6214/6254 |
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09:00 - 10:00
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Mao Fabrice Djete
(Ecole Polytechnique) Large population games with interactions through controls and common noise: the closed-loop case | Résumé |
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10:00 - 10:10
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Gokce Dayanikli
(Princeton University) Optimal Incentives in Mean Field Games: A numerical approach for the epidemic control problem | Résumé |
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10:10 - 10:20
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Cristian Mendico
(University of Rome Tor Vergata) Asymptotic behavior of solutions to first-order mean field games | Résumé |
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10:20 - 10:30
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Giulia Livieri
(Scuola Normale Superiore) N -player games and mean field games of moderate interactions | Résumé |
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10:30 - 11:00
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Pause-café
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Salle(s) 6245
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11:00 - 12:00
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Ludovic Tangpi
(Princeton University) Large population games in the weak formulation and their mean field game limits | Résumé |
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12:00 - 14:00
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14:00 - 15:00
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Wilfrid Gangbo
(UCLA) Global well posedness of master equations Mean Field Games | Résumé |
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15:00 - 16:00
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Yuchong Zhang
(University of Toronto) A mean field game of sequential testing | Résumé |
Le vendredi 15 avril 2022 |
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Salle(s) de réunion : 6214/6254 |
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09:30 - 10:30
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Alessio Porretta
(Università di Roma Tor Vergata) Adjoint methods and coupling in time-decay estimates | Résumé |
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10:30 - 11:00
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Pause-café
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Salle(s) 6245
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11:00 - 12:00
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Fernando Alvarez
(University of Chicago) On the structure of the linearization of MFGs with impulse controls | Résumé |
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12:00 - 14:00
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Déjeuner
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14:00 - 15:00
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Xin Guo
(UC Berkeley) Mean field multi agent reinforcement learning: a decentralized network approach | Résumé |
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15:00 - 16:00
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Pierre Cardaliaguet
(Université Paris-Dauphine) (Colloquium) Some aspects of Mean Field Games | Résumé |
Mise à jour: Le mardi 26 avril 2022 09:11