146 citations · 380 across the 19 of their papers we have counts for
21 papers
Learning in Time-Varying Monotone Network Games with Dynamic Populations
Feras Al Taha, Kiran Rokade, Francesca Parise
In this paper, we present a framework for multi-agent learning in a nonstationary dynamic network environment. More specifically, we examine projected gradient play in smooth monot…
Gradient Dynamics in Linear Quadratic Network Games with Time-Varying Connectivity and Population Fluctuation
Feras Al Taha, Kiran Rokade, Francesca Parise
In this paper, we consider a learning problem among non-cooperative agents interacting in a time-varying system. Specifically, we focus on repeated linear quadratic network games,…
Estimation of Unknown Payoff Parameters in Large Network Games
Feras Al Taha, Francesca Parise
We consider network games where a large number of agents interact according to a network sampled from a random network model, represented by a graphon. By exploiting previous resul…
Data-Driven Approximations of Chance Constrained Programs in Nonstationary Environments
Shuhao Yan, Francesca Parise, Eilyan Bitar
We study sample average approximations (SAA) of chance constrained programs. SAA methods typically approximate the actual distribution in the chance constraint using an empirical d…
Designing for Robustness in Electric Grids via a General Effective Resistance Measure
Shriya V. Nagpal, Gokul G. Nair, Francesca Parise +1
We propose a mathematical framework for designing robust networks of coupled phase-oscillators by leveraging a vulnerability measure proposed by Tyloo et. al that quantifies how mu…
Lockdown interventions in SIR model: Is the reproduction number the right control variable?
Leonardo Cianfanelli, Francesca Parise, Daron Acemoglu +2
The recent COVID-19 pandemic highlighted the need of non-pharmaceutical interventions in the first stages of a pandemic. Among these, lockdown policies proved unavoidable yet extre…
Accelerated consensus in multi-agent networks via memory of local averages
Aditya Bhaskar, Shriya Rangarajan, Vikram Shree +2
Classical mathematical models of information sharing and updating in multi-agent networks use linear operators. In the paradigmatic DeGroot model, agents update their states with l…
Optimal intervention in transportation networks
Leonardo Cianfanelli, Giacomo Como, Asuman Ozdaglar +1
We study a network design problem (NDP) where the planner aims at selecting the optimal single-link intervention on a transportation network to minimize the travel time under Wardr…
Optimal adaptive testing for epidemic control: combining molecular and serology tests
D. Acemoglu, A. Fallah, A. Giometto +4
The COVID-19 crisis highlighted the importance of non-medical interventions, such as testing and isolation of infected individuals, in the control of epidemics. Here, we show how t…
Fictitious play in zero-sum stochastic games
Muhammed O. Sayin, Francesca Parise, Asuman Ozdaglar
We present a novel variant of fictitious play dynamics combining classical fictitious play with Q-learning for stochastic games and analyze its convergence properties in two-player…
Optimal dynamic information provision in traffic routing
Emily Meigs, Francesca Parise, Asuman Ozdaglar +1
We consider a two-road dynamic routing game where the state of one of the roads (the "risky road") is stochastic and may change over time. This generates room for experimentation.…
On the Efficiency of Nash Equilibria in Aggregative Charging Games
Dario Paccagnan, Francesca Parise, John Lygeros
Several works have recently suggested to model the problem of coordinating the charging needs of a fleet of electric vehicles as a game, and have proposed distributed algorithms to…
Graphon games: A statistical framework for network games and interventions
Francesca Parise, Asuman Ozdaglar
In this paper, we present a unifying framework for analyzing equilibria and designing interventions for large network games sampled from a stochastic network formation process repr…
A variational inequality framework for network games: Existence, uniqueness, convergence and sensitivity analysis
Francesca Parise, Asuman Ozdaglar
We provide a unified variational inequality framework for the study of fundamental properties of the Nash equilibrium in network games. We identify several conditions on the underl…
Centrality measures for graphons: Accounting for uncertainty in networks
Marco Avella-Medina, Francesca Parise, Michael T. Schaub +1
As relational datasets modeled as graphs keep increasing in size and their data-acquisition is permeated by uncertainty, graph-based analysis techniques can become computationally…
Sensitivity analysis for network aggregative games
Francesca Parise, Asuman Ozdaglar
We investigate the sensitivity of the Nash equilibrium of constrained network aggregative games to changes in exogenous parameters affecting the cost function of the players. This…
A distributed algorithm for average aggregative games with coupling constraints
Francesca Parise, Basilio Gentile, John Lygeros
We consider the framework of average aggregative games, where the cost function of each agent depends on his own strategy and on the average population strategy. We focus on the ca…
Computing the projected reachable set of switched affine systems: an application to systems biology
Francesca Parise, Maria Elena Valcher, John Lygeros
A fundamental question in systems biology is what combinations of mean and variance of the species present in a stochastic biochemical reaction network are attainable by perturbing…
Nash and Wardrop equilibria in aggregative games with coupling constraints
Dario Paccagnan, Basilio Gentile, Francesca Parise +2
We consider the framework of aggregative games, in which the cost function of each agent depends on his own strategy and on the average population strategy. As first contribution,…
Network Aggregative Games and Distributed Mean Field Control via Consensus Theory
Francesca Parise, Sergio Grammatico, Basilio Gentile +1
We consider network aggregative games to model and study multi-agent populations in which each rational agent is influenced by the aggregate behavior of its neighbors, as specified…
Decentralized Convergence to Nash Equilibria in Constrained Deterministic Mean Field Control
Sergio Grammatico, Francesca Parise, Marcello Colombino +1
This paper considers decentralized control and optimization methodologies for large populations of systems, consisting of several agents with different individual behaviors, constr…