In this talk, we consider quasi-stationary Mean Field Games of Controls.
In these problems, the strategy-choice mechanism of the agent differs
from the classical one: the generic agent cannot predict the evolution
of the population and instead chooses its strategy based solely on the
information available at the current moment, without anticipating future
developments. Furthermore, the dynamics of an individual agent is
influenced not only by the distribution of agents but also by the
distribution of their optimal strategies.
We demonstrate the existence and uniqueness of the solution for the
corresponding quasi-stationary Mean Field Games system under various
sets of hypotheses and provide examples of models that fall within these
parameters.
