1 citations · 1 across the 4 of their papers we have counts for
4 papers
Multi-level Optimal Control with Neural Surrogate Models
Dante Kalise, Estefanía Loayza-Romero, Kirsten A. Morris +1
Optimal actuator and control design is studied as a multi-level optimisation problem, where the actuator design is evaluated based on the performance of the associated optimal clos…
Data-driven initialization of deep learning solvers for Hamilton-Jacobi-Bellman PDEs
Anastasia Borovykh, Dante Kalise, Alexis Laignelet +1
A deep learning approach for the approximation of the Hamilton-Jacobi-Bellman partial differential equation (HJB PDE) associated to the Nonlinear Quadratic Regulator (NLQR) problem…
Supervised learning for kinetic consensus control
Giacomo Albi, Sara Bicego, Dante Kalise
In this paper, how to successfully and efficiently condition a target population of agents towards consensus is discussed. To overcome the curse of dimensionality, the mean field f…
A Boltzmann approach to mean-field sparse feedback control
Giacomo Albi, Massimo Fornasier, Dante Kalise
We study the synthesis of optimal control policies for large-scale multi-agent systems. The optimal control design induces a parsimonious control intervention by means of l-1, spar…