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Country: Democratic Republic of the Congo
Submitted
Apr 12, 2024
Accepted
Jan 10, 2025
Published
Jan 10, 2025
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Abstract

This paper explores the use of fuzzy set theory to model the behavior of voters in a multi-agent electoral
environment. Voters, represented as fuzzy agents, communicate using imprecise language to form
communities based on shared linguistic terms. By leveraging graph theory, we construct a model of a
fuzzy voting system where agents are linked based on the similarity of their fuzzy language. The
proposed approach focuses on identifying, constructing, and extracting communities of fuzzy voters
without delving into their relational dynamics. Using fuzzy set membership functions, we define
linguistic variables that reflect the imprecision in voter behavior. The study introduces an algorithm to
detect communities by creating links between fuzzy voters, ultimately forming groups based on their
linguistic similarities. Results demonstrate that fuzzy communities can be successfully constructed,
where the membership function quantifies the degree of belonging of voters to specific communities.
This method contributes to a better understanding of voting behavior in complex, heterogeneous systems
and offers a novel approach to community detection in multi-agent systems

Keywords

Fuzzy Language Multiagent Systems Community Construction And Voter

Article Details

Lisensi Creative Commons
This work is licensed under a Lisensi Creative Commons Atribusi-BerbagiSerupa 4.0 Internasional.

How to Cite
[1]
M. Belangany, P. Kasengadia Motumbe, and E. Mbuyi Mukendi, “Multiagent Systems as an Approach to Building Fuzzy voter Communities using fuzzy languages”, bit-cs, vol. 6, no. 1, pp. 1-9, Jan. 2025.

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