Asymptotic Behavior of a Bounded Confidence Model with an Infinite Number of Agents

Student: Ignatovskaya Valeriya

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Control Systems and Data Processing in Engineering (Master)

Year of Graduation: 2020

We study the asymptotic properties of opinion dynamics models with an infinite number of agents. Modifications of the classical Hegselmann-Krause opinion dynamics model with bounded confidence, the classical DeGroot model, and some stochastic models with close asymptotic behavior are considered. We study asymptotic rates of formation of final clusters. Special metrics have been developed to compare qualitatively the closeness of configurations. These metrics are designed to develop a unified approach to the analytical and numerical analysis of the asymptotic behavior of configuration boundaries and the stability of the main indicators with respect to small random perturbations of initial configurations. We use Python to make numerical experiments and visualize opinion dynamics.

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