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All Journal Buana Information Technology and Computer Sciences (BIT and CS)
University of Kinshasa
Computer Science & IT

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T Taking Into Account Imprecision in the Modeling Voter in a Multi-Agent Environment
Buana Information Technology and Computer Sciences (BIT and CS) Vol. 5 No. 1 (2024): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v5i1.5800

Abstract

An electoral system is a set of individuals considered as agents in a multi-agent system in which voters communicate with each other and with the environment. In such a system, it is often difficult to understand the behavior of an agent that we call a voter. This is why, in this paper, we use fuzzy set theory as an approach to model the behavior of an imprecise voter in an electoral environment. It will be just a question of presenting a model of a voter with fuzzy behavior using mathematical approaches in this environment considered as a multi-agent environment and to propose the algorithms as the tools of computer modeling.
Multiagent Systems as an Approach to Building Fuzzy voter Communities using fuzzy languages: Author's Country: Democratic Republic of the Congo
Buana Information Technology and Computer Sciences (BIT and CS) Vol. 6 No. 1 (2025): Buana Information Technology and Computer Sciences (BIT and CS)
Publisher : Information System; Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/bit-cs.v6i1.6814

Abstract

This paper explores the use of fuzzy set theory to model the behavior of voters in a multi-agent electoralenvironment. Voters, represented as fuzzy agents, communicate using imprecise language to formcommunities based on shared linguistic terms. By leveraging graph theory, we construct a model of afuzzy voting system where agents are linked based on the similarity of their fuzzy language. Theproposed approach focuses on identifying, constructing, and extracting communities of fuzzy voterswithout delving into their relational dynamics. Using fuzzy set membership functions, we definelinguistic variables that reflect the imprecision in voter behavior. The study introduces an algorithm todetect communities by creating links between fuzzy voters, ultimately forming groups based on theirlinguistic 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 systemsand offers a novel approach to community detection in multi-agent systems
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