Abstract
Adaptive bounded-confidence models (ABCMs) elucidate the coevolution of agent states and network structure via local interactions and rewiring mechanisms. Traditional formulations assume uniform interaction parameters, leading to distinct regime shifts encompassing fragmentation, polarization, and consensus. A symmetric heterogeneous extension of the adaptive bounded-confidence model is introduced, in which interaction parameters vary according to whether agents belong to the same or different groups. The model retains the original update and rewiring protocols but integrates within-group and between-group confidence bounds alongside tolerance thresholds. Initially, the classic homogeneous model is replicated to establish a reference point. Subsequently, the heterogeneous extension is assessed under identical parameter settings. Findings reveal that symmetric parameter diversity upholds the fundamental regime progression while systematically adjusting transition thresholds and altering network configurations. The proposed framework offers a structured extension of ABCM, facilitating a direct contrast between homogeneous and heterogeneous interaction frameworks.
Recommended Citation
Hafez, Sally; Farag, Fatma R.; and Tawadros, Amira S. N.
()
"From Homogeneous to Heterogeneous Adaptive Bounded-Confidence Opinion Dynamics on Networks,"
Northeast Journal of Complex Systems (NEJCS): Vol. 8
:
No.
4
, Article 1.
DOI: https://doi.org/10.63562/2577-8439.1169
Available at:
https://orb.binghamton.edu/nejcs/vol8/iss4/1
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