Consensus in Complex Networks with Noisy Agents and Peer Pressure
arXiv:2306.14586 · doi:10.1016/j.physa.2022.128263
Abstract
In this paper we study a discrete time consensus model on a connected graph with monotonically increasing peer-pressure and noise perturbed outputs masking a hidden state. We assume that each agent maintains a constant hidden state and a presents a dynamic output that is perturbed by random noise drawn from a mean-zero distribution. We show consensus is ensured in the limit as time goes to infinity under certain assumptions on the increasing peer-pressure term and also show that the hidden state cannot be exactly recovered even when model dynamics and outputs are known. The exact nature of the distribution is computed for a simple two vertex graph and results found are shown to generalize (empirically) to more complex graph structures.
11 pages, 10 figures
References in corpus (6)
- Statistical physics of social dynamics
- Interaction Ruling Animal Collective Behaviour Depends on Topological rather than Metric Distance: Evidence from a Field Study
- Continuous Opinion Dynamics under Bounded Confidence: A Survey
- The Spontaneous Emergence of Conventions: An Experimental Study of Cultural Evolution
- Opinion dynamics: rise and fall of political parties
- Approach to consensus in models of continuous-opinion dynamics: a study inspired by the physics of granular gases