107 citations · 475 across the 51 of their papers we have counts for
8 papers · 1 filter
A polynomial approximation scheme for nonlinear model reduction by moment matching
Carlos Doebeli, Alessandro Astolfi, Dante Kalise +3
We propose a procedure for the numerical approximation of invariance equations arising in the moment matching technique associated with reduced-order modeling of high-dimensional d…
A total variation flow scheme for ergodic mean field games
Dante Kalise, Alessio Oliviero, Domènec Ruiz-Balet
Motivated by recent developments in mean field games in ecology, in this paper we introduce a connection between the best response dynamics in evolutionary game theory, the minimiz…
Fast and robust consensus-based optimization via optimal feedback control
Yuyang Huang, Michael Herty, Dante Kalise +1
We propose a variant of consensus-based optimization (CBO) algorithms, controlled-CBO, which introduces a feedback control term to improve convergence towards global minimizers of…
A multiscale Consensus-Based algorithm for multi-level optimization
Michael Herty, Yuyang Huang, Dante Kalise +1
A novel multiscale consensus-based optimization (CBO) algorithm for solving bi- and tri-level optimization problems is introduced. Existing CBO techniques are generalized by the pr…
Computation and Control of Unstable Steady States for Mean Field Multiagent Systems
Sara Bicego, Dante Kalise, Grigorios A. Pavliotis
We study interacting particle systems driven by noise, modeling phenomena such as opinion dynamics. We are interested in systems that exhibit phase transitions i.e. non-uniqueness…
Control of high-dimensional collective dynamics by deep neural feedback laws and kinetic modelling
Giacomo Albi, Sara Bicego, Dante Kalise
Modeling and control of agent-based models is twice cursed by the dimensionality of the problem, as both the number of agents and their state space dimension can be large. Even tho…
Data/moment-driven approaches for fast predictive control of collective dynamics
Giacomo Albi, Sara Bicego, Michael Herty +3
Feedback control synthesis for large-scale particle systems is reviewed in the framework of model predictive control (MPC). The high-dimensional character of collective dynamics ha…
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…