Stochastic optimal control and games have a wide range of applications, from finance and
economics to social sciences, robotics, and energy management. Many real-world …

The data traffic volume of the 6th generation (6G) mobile communication networks is huge,
and there are novel challenges in various communications services and scenarios. This …

Non-cooperative and cooperative games with a very large number of players have many
applications but remain generally intractable when the number of players increases …

Mean field games (MFG) and mean field control problems (MFC) are frameworks to study
Nash equilibria or social optima in games with a continuum of agents. These problems can …

Mean-field games (MFGs) have shown strong modeling capabilities for large systems in
various fields, driving growth in computational methods for mean-field game problems …

This paper proposes a new mathematical paradigm to analyze discrete-time mean-field
games. It is shown that finding Nash equilibrium solutions for a general class of discrete-time …

We propose several algorithms to solve McKean-Vlasov Forward Backward Stochastic
Differential Equations (FBSDEs). Our schemes rely on the approximating power of neural …

Financial markets and more generally macro-economic models involve a large number of
individuals interacting through variables such as prices resulting from the aggregate …

We introduce two algorithms based on a policy iteration method to numerically solve time-
dependent Mean Field Game systems of partial differential equations with non-separable …

The most serious threat to ecosystems is the global climate change fueled by the
uncontrolled increase in carbon emissions. In this project, we use mean field control and …