Vol.70, No.3, 2022, pp.6305-6321, doi:10.32604/cmc.2022.021804
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ARTICLE
Extremal Coalitions for Influence Games Through Swarm Intelligence-Based Methods
  • Fabián Riquelme1,*, Rodrigo Olivares1, Francisco Muñoz1, Xavier Molinero3, Maria Serna2
1 Escuela de Ingeniería Informática, Universidad de Valparaíso, Valparaíso, Chile
2 Computer Science Department, Universitat Politècnica de Catalunya, Barcelona, Spain
3 Mathematics Department, Universitat Politècnica de Catalunya, Terrassa, Spain
* Corresponding Author: Fabián Riquelme. Email:
(This article belongs to this Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Received 14 July 2021; Accepted 19 August 2021; Issue published 11 October 2021
Abstract
An influence game is a simple game represented over an influence graph (i.e., a labeled, weighted graph) on which the influence spread phenomenon is exerted. Influence games allow applying different properties and parameters coming from cooperative game theory to the contexts of social network analysis, decision-systems, voting systems, and collective behavior. The exact calculation of several of these properties and parameters is computationally hard, even for a small number of players. Two examples of these parameters are the length and the width of a game. The length of a game is the size of its smaller winning coalition, while the width of a game is the size of its larger losing coalition. Both parameters are relevant to know the levels of difficulty in reaching agreements in collective decision-making systems. Despite the above, new bio-inspired metaheuristic algorithms have recently been developed to solve the NP-hard influence maximization problem in an efficient and approximate way, being able to find small winning coalitions that maximize the influence spread within an influence graph. In this article, we apply some variations of this solution to find extreme winning and losing coalitions, and thus efficient approximate solutions for the length and the width of influence games. As a case study, we consider two real social networks, one formed by the 58 members of the European Union Council under nice voting rules, and the other formed by the 705 members of the European Parliament, connected by political affinity. Results are promising and show that it is feasible to generate approximate solutions for the length and width parameters of influence games, in reduced solving time.
Keywords
Influence game; influence spread; collective behavior; swarm intelligence; bio-inspired computing
Cite This Article
Riquelme, F., Olivares, R., Muñoz, F., Molinero, X., Serna, M. (2022). Extremal Coalitions for Influence Games Through Swarm Intelligence-Based Methods. CMC-Computers, Materials & Continua, 70(3), 6305–6321.
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