LQG mean field games with a major agent: Nash certainty equivalence versus probabilistic approach
Dena Firoozi – Assistant Professor, Department of Decision Sciences, HEC Montréal, Canada
Webinar link
Webinar ID: 910 7928 6959
Passcode: VISS
Mean field game systems consisting of a major agent and a large population of minor agents were introduced in (Huang, 2010) in an LQG setup. In the past years several approaches towards major-minor mean field games have been developed, principally (i) the Nash certainty equivalence (Huang, 2010), (ii) master equations, (iii) asymptotic solvability, and (iv) the probabilistic approach. In a recent work (Huang, 2020), for the LQG case the equivalence of the solutions obtained via approaches (i)-(iii) was established. In this talk we first review approaches (i) and (iv). We then demonstrate that the closed-loop Nash equilibrium derived in the infinite-population limit through (i) and (iv) are identical.
Biography: Dena Firoozi is an Assistant Professor in the Department of Decision Sciences at HEC Montréal (business school of University of Montreal). Before joining HEC Montréal, she was a postdoctoral fellow in the mathematical finance program of the Department of Statistical Sciences at the University of Toronto, Canada, between 2018-2020. She was also a PhD exchange student in the same program during Fall 2017. She received her Ph.D. degree in electrical engineering, systems & control specialization, from McGill University, Canada, in 2019. Dena’s research interests are in mean field games, stochastic control, estimation theory, and their applications in financial and energy markets.
Location
Montréal Québec
Canada