Data clustering as an emergent consensus of autonomous agents

We present a data segmentation method based on a first-order density-induced consensus protocol. We provide a mathematically rigorous analysis of the consensus model leading to stopping criteria of the data segmentation algorithm. To illustrate our method

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Publication Details

Journal
Applicationes Mathematicae
Published
2025-01-01
DOI
https://doi.org/10.4064/am2507-2-2025
Primary Topic
Data Mining Algorithms and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Data clustering as an emergent consensus of autonomous agents

Jan Peszek, Piotr Minakowski
Applicationes Mathematicae
Data Mining Algorithms and Applications
article

Data clustering as an emergent consensus of autonomous agents

Jan Peszek, Piotr Minakowski
article en

Abstract

We present a data segmentation method based on a first-order density-induced consensus protocol. We provide a mathematically rigorous analysis of the consensus model leading to stopping criteria of the data segmentation algorithm. To illustrate our method

Applicationes MathematicaeVol. 52(1)
University of Warsaw (PL), Otto-von-Guericke-Universität Magdeburg (DE)
Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Narodowe Centrum Nauki
Reduced inequalities
Openalex Percentile: Top 85%
Data Mining Algorithms and Applications
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