154 citations · 404 across the 11 of their papers we have counts for
12 papers
Estimation Network Design framework for efficient distributed optimization
Mattia Bianchi, Sergio Grammatico
Distributed decision problems features a group of agents that can only communicate over a peer-to-peer network, without a central memory. In applications such as network control an…
Linear convergence in time-varying generalized Nash equilibrium problems
Mattia Bianchi, Emilio Benenati, Sergio Grammatico
We study generalized games with full row rank equality constraints and we provide a strikingly simple proof of strong monotonicity of the associated KKT operator. This allows us to…
Data-driven stabilization of switched and constrained linear systems
Mattia Bianchi, Sergio Grammatico, Jorge Cortés
We consider the design of state feedback control laws for both the switching signal and the continuous input of an unknown switched linear system, given past noisy input-state traj…
The END: Estimation Network Design for games under partial-decision information
Mattia Bianchi, Sergio Grammatico
Multi-agent decision problems are typically solved via distributed iterative algorithms, where the agents only communicate between themselves on a peer-to-peer network. Each agent…
Nash equilibrium seeking under partial decision information: Monotonicity, smoothness and proximal-point algorithms
Mattia Bianchi, Sergio Grammatico
We address Nash equilibrium problems in a partial-decision information scenario, where each agent can only exchange information with some neighbors, while its cost function possibl…
The distributed dual ascent algorithm is robust to asynchrony
Mattia Bianchi, Wicak Ananduta, Sergio Grammatico
The distributed dual ascent is an established algorithm to solve strongly convex multi-agent optimization problems with separable cost functions, in the presence of coupling constr…
Nash equilibrium seeking under partial-decision information over directed communication networks
Mattia Bianchi, Sergio Grammatico
We consider the Nash equilibrium problem in a partial-decision information scenario. Specifically, each agent can only receive information from some neighbors via a communication n…
Fully distributed Nash equilibrium seeking over time-varying communication networks with linear convergence rate
Mattia Bianchi, Sergio Grammatico
We design a distributed algorithm for learning Nash equilibria over time-varying communication networks in a partial-decision information scenario, where each agent can access its…
Fast generalized Nash equilibrium seeking under partial-decision information
Mattia Bianchi, Giuseppe Belgioioso, Sergio Grammatico
We address the generalized Nash equilibrium seeking problem in a partial-decision information scenario, where each agent can only exchange information with some neighbors, although…
Continuous-time fully distributed generalized Nash equilibrium seeking for multi-integrator agents
Mattia Bianchi, Sergio Grammatico
We consider strongly monotone games with convex separable coupling constraints, played by dynamical agents, in a partial-decision information scenario. We start by designing contin…
A fully-distributed proximal-point algorithm for Nash equilibrium seeking with linear convergence rate
Mattia Bianchi, Giuseppe Belgioioso, Sergio Grammatico
We address the Nash equilibrium problem in a partial-decision information scenario, where each agent can only observe the actions of some neighbors, while its cost possibly depends…
A continuous-time distributed generalized Nash equilibrium seeking algorithm over networks for double-integrator agents
Mattia Bianchi, Sergio Grammatico
We consider a system of single- or double integrator agents playing a generalized Nash game over a network, in a partial-information scenario. We address the generalized Nash equil…