We investigate a class of network games with strategic complements and congestion effects, by using the variational inequality approach. Our contribution is twofold. We first express the boundary components of the Nash equilibrium by means of the Katz-Bonacich centrality measure. Then, we propose a new ranking of the network nodes based on the social welfare at equilibrium and compare this solution-based ranking with some classical topological ranking methods.

Passacantando, M., Raciti, F. (2022). A Variational Inequality Approach to a Class of Network Games with Local Complementarities and Global Congestion. In L. Amorosi, P. Dell’Olmo, I. Lari (a cura di), Optimization in Artificial Intelligence and Data Sciences (pp. 1-11). Springer [10.1007/978-3-030-95380-5_1].

A Variational Inequality Approach to a Class of Network Games with Local Complementarities and Global Congestion

Passacantando, M;
2022

Abstract

We investigate a class of network games with strategic complements and congestion effects, by using the variational inequality approach. Our contribution is twofold. We first express the boundary components of the Nash equilibrium by means of the Katz-Bonacich centrality measure. Then, we propose a new ranking of the network nodes based on the social welfare at equilibrium and compare this solution-based ranking with some classical topological ranking methods.
Capitolo o saggio
Nash equilibrium; Network centrality measures; Network games; Social welfare;
English
Optimization in Artificial Intelligence and Data Sciences
Amorosi, L; Dell’Olmo, P; Lari, I
2022
978-3-030-95379-9
8
Springer
1
11
Passacantando, M., Raciti, F. (2022). A Variational Inequality Approach to a Class of Network Games with Local Complementarities and Global Congestion. In L. Amorosi, P. Dell’Olmo, I. Lari (a cura di), Optimization in Artificial Intelligence and Data Sciences (pp. 1-11). Springer [10.1007/978-3-030-95380-5_1].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/391589
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