Ergodic control of McKean-Vlasov systems on the Wasserstein space

Abstract

We consider an optimal control problem with ergodic (long term average) reward for a McKean-Vlasov dynamics, where the coefficients of a controlled stochastic differential equation depend on the marginal law of the solution. Starting from the associated infinite time horizon expected discounted reward, we construct both the value $\lambda$ of the ergodic problem and an associated function $\phi$, which provide a viscosity solution to an ergodic Hamilton-Jacobi-Bellman (HJB) equation of elliptic type. In contrast to previous results, we consider the function $\phi$ and the HJB equation on the Wasserstein space, using concepts of derivatives with respect to probability measures. The pair $(\lambda,\phi)$ also provides information on limit behavior of related optimization problems, for instance, results of Abelian-Tauberian type or limits of value functions of control problems for finite time horizon when the latter tends to infinity. Many arguments are simplified by the use of a functional relation for $\phi$ in the form of a suitable dynamic programming principle.