Séminaire de Tembine Hamidou
Il y a: 57 days
Salle de séminaire (4B05R) - Bâtiment Copernic
The term "mean-field" has been referred to a physics concept that attempts to describe the effect of an infinite number of particles on the motion of a single particle. Researchers began to apply the concept to social sciences in the early 1960s to study how an infinite number of factors affect individual decisions. However, the key ingredient in a game-theoretic context is the influence of the distribution of states and or control actions into the payoffs of the decision-makers. There is no need to have large population of decision-makers. A mean-field-type game is a game in which the payoffs and/or the state dynamics coefficient functions involve not only the state and actions profiles but also the distributions of state-action process (or its marginal distributions). In this talk, we overview the key ingredients of mean-field-type game theory.
Tembine Hamidou received the M.S. degree in Applied Mathematics from Ecole Polytechnique (Palaiseau, Paris, France) in 2006 and the Ph.D. degree in Computer Science from University of Avignon in 2009. His current research interests include evolutionary games, mean-field stochastic games and applications. In December 2014, Tembine received the IEEE ComSoc Outstanding Young Researcher Award for his promising research activities for the benefit of the society. He was the recipient of 7 best article awards in the applications of game theory. Tembine is a prolific researcher and holds several scientific publications including magazines, letters, journals and conferences. He is author of the book on "distributed strategic learning for engineers" (published by CRC Press, Taylor & Francis 2012), and co-author of the book "Game Theory and Learning in Wireless Networks" (Elsevier Academic Press). Tembine has been co-organizer of several scientific meetings on game theory in networking, wireless communications, smart energy and transportation systems. He is a senior member of IEEE.