This paper is devoted to the study of multi-agent deterministic optimal control problems. We
initially provide a thorough analysis of the Lagrangian, Eulerian and Kantorovich …

We derive novel algorithms for optimization problems constrained by partial differential
equations describing multiscale particle dynamics, including non-local integral terms …

We analyze a problem of optimal control of the Fokker-Planck equation with state constraints
in the Wasserstein space of probability measures. We give first-order necessary conditions …

The narrowband Internet of Things (NB-IoT) is a cellular technology introduced by the third-
generation partnership project (3GPP) to provide connectivity to a large number of low-cost …

We analyze the problem of controlling a multiagent system with additive white noise through
parsimonious interventions on a selected subset of the agents (leaders). For such a …

Motivated by the applications in leader-follower multi-agent dynamics, a class of optimal
control problems is investigated, where the goal is to influence the behavior of a given …

We provide a rigorous mathematical formulation of Deep Learning (DL) methodologies
through an in-depth analysis of the learning procedures characterizing Neural Network (NN) …

We consider a control problem for the nonlinear stochastic Fokker--Planck equation. This
equation describes the evolution of the distribution of nonlocally interacting particles affected …

We derive novel algorithms for optimization problems constrained by partial differential
equations describing multiscale particle dynamics, including non-local integral terms …

The mean-field control problem for a multi-dimensional diffusion-aggregation system with
Coulomb interaction (the so called parabolic elliptic Keller-Segel system) is considered. The …