The goal of this work is to obtain (nearly) optimal rates for the convergence problem in mean
field control. Our analysis covers cases where the solutions to the limiting problem may not …

We establish an algebraic rate of convergence of the value functions of-particle stochastic
control problems towards the value function of the corresponding McKean–Vlasov problem …

We study high-dimensional stochastic optimal control problems in which many agents
cooperate to minimize a convex cost functional. We consider both the full-information …

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 investigate a mean field optimal control problem obtained in the limit of the optimal
control of large particle systems with forcing and terminal data which are not assumed to be …

We study stochastic teams (known also as decentralized stochastic control problems or
identical interest stochastic dynamic games) with large or countably infinite numbers of …

This paper analyzes the convergence of the finite population optimal stopping problem
towards the corresponding mean field limit. Building on the viscosity solution …

We study the convergence problem for mean field control, also known as optimal control of
McKean-Vlasov dynamics. We assume that the data is smooth but not convex, and thus the …

We investigate propagation of chaos for mean field Markov Decision Process with common
noise (CMKV-MDP), and when the optimization is performed over randomized open-loop …

We study a class of stochastic exchangeable teams comprising a finite number of decision
makers (DMs) as well as their mean-field limits involving infinite numbers of DMs. In the finite …