A variational approach to the mean field planning problem

We investigate a first-order mean field planning problem associated to a convex Hamiltonian H with quadratic growth and a monotone interaction term f with polynomial growth.

We exploit the variational structure of the system, which encodes the first order optimality condition of a convex dynamic optimal entropy-transport problem with respect to the unknown density m and of its dual, involving the maximization of an integral functional among all the subsolutions u of an Hamilton-Jacobi equation.

Combining ideas from optimal transport, convex analysis and renormalized solutions to the continuity equation, we will prove existence and (at least partial) uniqueness of a weak solution. A crucial step of our approach relies on a careful analysis of distributional subsolutions to Hamilton-Jacobi equations of the form , under minimal summability conditions on α, and to a measure-theoretic description of the optimality via a suitable contact-defect measure. Finally, using the superposition principle, we are able to describe the solution to the system by means of a measure on the path space encoding the local behavior of the players.