activity
20192024
most citedWhen Nash Meets Stackelberg

11 citations · 23 across the 8 of their papers we have counts for

collaborators

9 papers

cs.RO2024

Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots

Haimin Hu, Gabriele Dragotto, Zixu Zhang +3

We consider the multi-agent spatial navigation problem of computing the socially optimal order of play, i.e., the sequence in which the agents commit to their decisions, and its as…

math.OC2023★ 1 cited

Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization

Gabriele Dragotto, Stefan Clarke, Jaime Fernández Fisac +1

We consider the problem of solving a family of parametric mixed-integer linear optimization problems where some entries in the input data change. We introduce the concept of cuttin…

math.OC2023★ 1 cited

Integer Programming Games: A Gentle Computational Overview

Margarida Carvalho, Gabriele Dragotto, Andrea Lodi +1

In this tutorial, we present a computational overview on computing Nash equilibria in Integer Programming Games (s), , how to compute solutions for a class of non-cooper…

math.OC2023

Learning Rationality in Potential Games

Stefan Clarke, Gabriele Dragotto, Jaime Fernández Fisac +1

We propose a stochastic first-order algorithm to learn the rationality parameters of simultaneous and non-cooperative potential games, i.e., the parameters of the agents' optimizat…

math.OC2023

The Critical Node Game

Gabriele Dragotto, Amine Boukhtouta, Andrea Lodi +1

In this work, we introduce a game-theoretic model that assesses the cyber-security risk of cloud networks and informs security experts on the optimal security strategies. Our appro…

math.OC2021★ 3 cited

The ZERO Regrets Algorithm: Optimizing over Pure Nash Equilibria via Integer Programming

Gabriele Dragotto, Rosario Scatamacchia

Designing efficient algorithms to compute Nash equilibria poses considerable challenges in Algorithmic Game Theory and Optimization. In this work, we employ integer programming tec…

math.OC2021

The Cut-and-Play Algorithm: Computing Nash Equilibria via Outer Approximations

Margarida Carvalho, Gabriele Dragotto, Andrea Lodi +1

We introduce Cut-and-Play, a practically-efficient algorithm for computing Nash equilibria in simultaneous non-cooperative games where players decide via nonconvex and possibly unb…

cs.GT2019★ 11 cited

When Nash Meets Stackelberg

Margarida Carvalho, Gabriele Dragotto, Felipe Feijoo +2

This article introduces a class of games among players (), namely, a class of simultaneous non-cooperative games where the players solve sequential Stac…

math.CO2019★ 7 cited

Merging Combinatorial Design and Optimization: the Oberwolfach Problem

Fabio Salassa, Gabriele Dragotto, Tommaso Traetta +2

The Oberwolfach Problem -- posed by Gerhard Ringel in 1967 -- is a paradigmatic Combinatorial Design problem asking whether the complete graph decomposes into edge-di…