Date and Time: Friday, August 14, 2020 at 1300 AEST
Speaker: Julian Barreiro-Gomez, New York University, Abu Dhabi Campus
Title: Mean-Field-Type Games: Risk-Aware Interactive Decision-Making Made Easy
Abstract: The term mean-field has been referred to as 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. Games with distribution-dependent quantity-of-interest such as state and or payoffs are particularly attractive because they capture not only the mean, but also the variance and higher order terms. The incorporation of these mean and variance terms is associated with the paradigm introduced by H. Markowitz, 1990 Nobel Laureate in Economics.
In this talk, we address variance reduction problems when several decision-making entities are involved. We briefly discuss about the modeling of the COVID-19 propagation and its control of mean-field type.
Biography: Julian Barreiro-Gomez received his B.S. degree (cum laude) in Electronics Engineering from Universidad Santo Tomas (USTA), Bogota, Colombia, in 2011. He received the MSc. degree in Electrical Engineering and the Ph.D. degree in Engineering from Universidad de Los Andes (UAndes), Bogota, Colombia, in 2013 and 2017, respectively. He received the Ph.D. degree (cum laude) in Automatic, Robotics and Computer Vision from the Technical University of Catalonia (UPC), Barcelona, Spain, in 2017; the best Ph.D. thesis in control engineering 2017 award from the Spanish National Committee of Automatic Control (CEA) and Springer; and the EECI Ph.D. Award from the European Embedded Control Institute in recognition to the best Ph.D. thesis in Europe in the field of Control for Complex and Heterogeneous Systems 2017. He received the ISA Transactions Best Paper Award 2018 in Recognition to the best paper published in the previous year. He is currently a Post-Doctoral Associate in the Learning & Game Theory Laboratory and in the Research Center on Stability, Instability and Turbulence at the New York University in Abu Dhabi (NYUAD). His main research interests are: Mean-field-type Games, Risk-Aware Control, Constrained Evolutionary Game Dynamics, and Distributed Optimization.