Abstract
Game theory has become a powerful tool in engineering field to study, model and control interacting systems. This talk addresses two game theoretical approaches, i.e., evolutionary games and mean-field-type games. First, Evolutionary Dynamics (ED) are introduced together with other extensions such as their respective distributed and/or constrained versions. It is shown how evolutionary dynamics are suitable algorithms for solving resource allocation problems under different communication structures. On the other hand, Linear-Quadratic Mean-Field-Type Games (LQ-MFTG) are introduced and solved by means of the Direct Method for different cases, e.g., under non-cooperative, cooperative and co-opetitive scenarios. We discuss about how ED and LQ-MFTG could complement to each other in order to solve further problems, and some engineering applications are presented.
Brief 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 at the New York University in Abu Dhabi (NYUAD), United Arab Emirates. His main research interests are Mean-field-type Games, Constrained Evolutionary Game Dynamics, Distributed Optimization, and Distributed Predictive Control.