3 papers
math.OC2026
A Distributed Bilevel Framework for the Macroscopic Optimization of Multi-Agent Systems
Riccardo Brumali, Guido Carnevale, Sonia MartÃnez +1
In this paper, we propose a novel distributed algorithm to optimize the emergent macroscopic behavior of large-scale multi-agent systems via microscopic actions. We cast this task…
math.OC2026
Model-Free Aggregative Cooperative Optimization via Randomized Gradient-Free Minimization and Exploration Momentum
Amir Mehrnoosh, Giuseppe Speciale, Riccardo Brumali +2
Aggregative cooperative optimization problems arise in distributed decision-making settings where each agent's objective depends on its own decision as well as on an aggregate vari…
math.OC2026
Data-Driven Distributed Optimization via Aggregative Tracking and Deep-Learning
Riccardo Brumali, Guido Carnevale, Giuseppe Notarstefano
In this paper, we propose a novel distributed data-driven optimization scheme. In detail, we focus on the so-called aggregative framework, a scenario in which a set of agents aim t…