Analysis of Consensus and Clustering Conditions in a Bounded Confidence Model

Student: Gorokhovskaya Olesya

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

Educational Programme: Applied Mathematics (Bachelor)

Year of Graduation: 2020

We consider the Hegselman – Krause opinion dynamics model with bounded confidence. We study the conditions, when a group of interacting agents reaches a consensus or clustering of opinions. We analyze stochastic properties and characteristics of the system and the dependence of agent’s behavior on the model parameters. The analytical estimates that consensus will not be approached are obtained. All analytical results were confirmed by computer modelling. Confidence intervals, which correspond to qualitatively different system dynamic, are identified.

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