Large population games with interactions through controls and common noise: convergence results and equivalence between $open$--$loop$ and $closed$--$loop$ controls

Abstract

In the presence of a common noise, we study the convergence problems in mean field game (MFG) and mean field control (MFC) problem where the cost function and the state dynamics depend upon the joint conditional distribution of the controlled state and the control process. In the first part, we consider the MFG setting. We start by recalling the notions of $measure$--$valued$ MFG equilibria and of approximate $closed$--$loop$ Nash equilibria associated to the corresponding $N$--player game. Then, we show that all convergent sequences of approximate $closed$--$loop$ Nash equilibria, when $N \to \infty,$ converge to $measure$--$valued$ MFG equilibria. And conversely, any $measure$--$valued$ MFG equilibrium is the limit of a sequence of approximate $closed$--$loop$ Nash equilibria. In other words, $measure$--$valued$ MFG equilibria are the accumulation points of the approximate $closed$--$loop$ Nash equilibria. Previous work has shown that $measure$--$valued$ MFG equilibria are the accumulation points of the approximate $open$--$loop$ Nash equilibria. Therefore, we obtain that the limits of approximate $closed$--$loop$ Nash equilibria and approximate $open$--$loop$ Nash equilibria are the same. In the second part, we deal with the MFC setting. After recalling the $closed$--$loop$ and $open$--$loop$ formulations of the MFC problem, we prove that they are equivalent. We also provide some convergence results related to approximate $closed$--$loop$ Pareto equilibria.