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Updated: May 13, 2026
06:48
The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
Topological analysis of group fragmentation in multiagent systems
Pietro DeLellis1, Maurizio Porfiri, Erik M Bollt
1Department of Systems and Computer Engineering, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy. pietro.delellis@unina.it
Summary
This study introduces a novel method to quantify group fragmentation in social animals using manifold embedding and topological analysis. This approach objectively measures subgroup formation, aiding in understanding collective behavior dynamics.
Area of Science:
- Collective behavior
- Animal social dynamics
- Computational ethology
Background:
- Social animals often form subgroups due to conflicts or multiple leaders.
- Objective quantification of group fragmentation is currently lacking.
- Understanding subgroup dynamics is crucial for studying collective behavior.
Purpose of the Study:
- To develop a quantitative method for detecting and measuring group fragmentation.
- To explore the use of manifold embedding and topological analysis for this purpose.
- To assess the feasibility of real-time fragmentation analysis.
Main Methods:
- Embedding individual motion data onto a low-dimensional manifold using the isomap algorithm.
- Analyzing the topological features of the manifold to identify subgroups.
- Implementing an interpolation method for real-time analysis.
Main Results:
- The dimensionality of the embedding manifold directly correlates with the number of subgroups.
- Cluster analysis aids in interpreting the topological findings.
- An interpolation technique enables real-time characterization of group fragmentation.
Conclusions:
- Manifold embedding provides an objective measure of group fragmentation.
- The proposed method offers a computationally efficient approach for real-time analysis.
- This technique has potential applications in regulating collective animal behavior.
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