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Main Authors: Song, Chen, Fontan, Angela, Su, Rong, Hendrickx, Julien M., Cvetkovic, Vladimir, Johansson, Karl H.
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.06140
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author Song, Chen
Fontan, Angela
Su, Rong
Hendrickx, Julien M.
Cvetkovic, Vladimir
Johansson, Karl H.
author_facet Song, Chen
Fontan, Angela
Su, Rong
Hendrickx, Julien M.
Cvetkovic, Vladimir
Johansson, Karl H.
contents This paper presents a theoretical convergence analysis for an opinion-action coevolution model that integrates the opinion updating rule of the Hegselmann-Krause model with a utility-based decision-making mechanism. The model is reformulated into an augmented state-space representation, where the state matrix induces a time-varying social interaction digraph. The convergence analysis is grounded on two existing theoretical findings that establish convergence for the Hegselmann-Krause type of models and containment control systems with multiple stationary leaders, respectively. Results indicate that, if the structure of the interaction digraph stabilizes within finite time, the model either converges to consensus, where all agents' opinions and actions reach an identical state, or exhibits clustering, where some opinion nodes act as stationary leaders while the remaining nodes approach the convex hull formed by the leaders. Numerical simulations are then provided to validate the theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2604_06140
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle On the Convergence of an Opinion-Action Coevolution Model with Bounded Confidence
Song, Chen
Fontan, Angela
Su, Rong
Hendrickx, Julien M.
Cvetkovic, Vladimir
Johansson, Karl H.
Systems and Control
This paper presents a theoretical convergence analysis for an opinion-action coevolution model that integrates the opinion updating rule of the Hegselmann-Krause model with a utility-based decision-making mechanism. The model is reformulated into an augmented state-space representation, where the state matrix induces a time-varying social interaction digraph. The convergence analysis is grounded on two existing theoretical findings that establish convergence for the Hegselmann-Krause type of models and containment control systems with multiple stationary leaders, respectively. Results indicate that, if the structure of the interaction digraph stabilizes within finite time, the model either converges to consensus, where all agents' opinions and actions reach an identical state, or exhibits clustering, where some opinion nodes act as stationary leaders while the remaining nodes approach the convex hull formed by the leaders. Numerical simulations are then provided to validate the theoretical results.
title On the Convergence of an Opinion-Action Coevolution Model with Bounded Confidence
topic Systems and Control
url https://arxiv.org/abs/2604.06140