The consensus problem for opinion dynamics with local average random interactions
Gianfelice Michele, Giuseppe Scola

TL;DR
This paper investigates a probabilistic opinion dynamics model where agents' communication links switch on or off randomly based on opinion proximity, proving geometric convergence to consensus under certain connectivity conditions.
Contribution
It generalizes Krause's model by incorporating random, proximity-dependent communication, and proves geometric consensus formation for finite and infinite agent systems.
Findings
Agents reach consensus at a geometric rate under sufficient initial connectivity.
The model's probabilistic communication depends on opinion proximity.
Consensus is achieved quickly both in finite and infinite agent systems.
Abstract
We study the consensus formation for an agents based model, generalizing that originally proposed by Krause \cite{Kr}, by allowing the communication channels between any couple of agents to be switched on or off randomly, at each time step, with a probability law depending on the proximity of the agents' opinions. Namely, we consider a system of agents sharing their opinions according to the following updating protocol. At time the opinion of any agent is updated at the weighted average of the opinions of the agents communicating with it at time The weights model the confidence level an agent assigns to the opinions of the other agents and are kept fixed by the system dynamics, but the set of agents communicating with any agent at time is randomly updated in such a way that the agent can be chosen to belong to…
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Taxonomy
TopicsOpinion Dynamics and Social Influence · Complex Network Analysis Techniques · Quantum chaos and dynamical systems
