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X-WR-CALDESC:DeustoCCM - Chair of Computational Mathematics at University of Deusto
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UID:MEC-12c61971537803cd33dd937236b9a8cb@cmc.deusto.eus
DTSTART:20210225T093000Z
DTEND:20210225T103000Z
DTSTAMP:20251031T223900Z
CREATED:20251031
LAST-MODIFIED:20251031
PRIORITY:5
TRANSP:OPAQUE
SUMMARY:Spatially inhomogeneous evolutionary games
DESCRIPTION:Speaker: Prof. Dr. Marco Morandotti\nAffiliation: Politecnico di Torino, Italy\nOrganized by: FAU CAA-AvH, Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany)\nRequest Zoom meeting link\nAbstract. We study an interaction model of a large population of players based on an evolutionary game, which describes the dynamical process of how the distribution of strategies changes in time according to their individual success. We assume that the population of players is distributed over a state space and that they are each endowed with probability distributions of pure strategies, which they draw at random to evolve their states. Simultaneously, the mixed strategies evolve according to a replicator dynamics, modeling the success of pure strategies according to a payoff functional. We establish existence, uniqueness, and stability of Lagrangian and Eulerian solutions of this dynamical game by using methods of ODE and optimal transport on Banach spaces. We apply the general theoretical framework to perform the mean-field analysis of a multi-population agent-based model, where a particle dynamics derived by a nonlocal velocity and a Markov-type jump process for the labels are coupled. An alternate Lagrangian approximation scheme at discrete times is also proposed.\nThis research is from joint works with S. Almi, L. Ambrosio, M. Fornasier, G. Savaré, and F. Solombrino.\n
URL:https://cmc.deusto.eus/events-calendar/spatially-inhomogeneous-evolutionary-games/
CATEGORIES:FAU CAA Seminar
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