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 theory of mean field games (MFGs) studies the limiting behaviors of large systems
where the agents interact with each other in a certain symmetric way. The running and …

In this work, we consider a novel inverse problem in mean-field games (MFGs). We aim to
recover the MFG model parameters that govern the underlying interactions among the …

We develop an exhaustive study of Markov decision process (MDP) under mean field
interaction both on states and actions in the presence of common noise, and when …

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 …

This paper studies the convergence problem for mean field games with common noise. We
define a suitable notion of weak mean field equilibria, which we prove captures all …

In this paper, we study graphon mean field games using a system of forward–backward
stochastic differential equations. We establish the existence and uniqueness of solutions …

We consider a jump-diffusion mean field control problem with regime switching in the state
dynamics. The corresponding value function is characterized as the unique viscosity …

We study the convergence problem for mean field games with common noise and controlled
volatility. We adopt the strategy recently put forth by Laurière and the second author, using …

In this paper, we study the extended mean field control problem, which is a class of McKean–
Vlasov stochastic control problem where the state dynamics and the reward functions …