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Practical consensus in bounded confidence opinion dynamics
Automatica ( IF 6.4 ) Pub Date : 2021-05-08 , DOI: 10.1016/j.automatica.2021.109683
Francesco Vasca , Carmela Bernardo , Raffaele Iervolino

Opinion dynamics expressed by the bounded confidence discrete-time heterogeneous Hegselmann–Krause model is considered. A policy for the adaptation of the agents confidence thresholds based on heterophily, maximum number of neighbors and non-influencing similarity interval is proposed. The policy leads to the introduction of the concepts of practical clustering and practical consensus. Several properties of the agents dynamic behaviors are proved by exploiting the roles of the agents having at each time-step the maximum and the minimum opinions. The convergence in finite time to (a maximum number of) practical clusters and, for sufficiently large threshold bounds, the convergence to a practical consensus are proved. Sufficient conditions for reaching a practical consensus around a stubborn are derived too. Numerical simulations verify the theoretical results.



中文翻译:

有限信心意见动态中的实践共识

考虑了由有限置信度离散时间异构Hegselmann-Krause模型表示的意见动态。提出了一种基于异质性,最大邻居数和不影响相似区间的Agent置信度阈值自适应策略。该政策导致引入了实用群集和实用共识的概念。通过利用在每个时间步长具有最大和最小意见的代理的角色,证明了代理动态行为的几个属性。证明了在有限时间内收敛到(最大数量的)实际簇,并且对于足够大的阈值边界,证明了收敛到实际共识。也得出了在顽固问题上达成实际共识的充分条件。

更新日期:2021-05-08
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