A quadratic lower bound for the convergence rate in the one-dimensional Hegselmann-Krause bounded confidence dynamics
Artikel i vetenskaplig tidskrift, 2015

Let f_{k}(n) be the maximum number of time steps taken to reach equilibrium by a system of n agents obeying the $k$-dimensional Hegselmann-Krause bounded confidence dynamics. Previously, it was known that \Omega(n) = f_{1}(n) = O(n^3). Here we show that f_{1}(n) = \Omega(n^2), which matches the best-known lower bound in all dimensions k >= 2.

Convergence rate

Dumbbell graph

Hegselmann–Krause Model

Författare

Edvin Wedin

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet

Peter Hegarty

Chalmers, Matematiska vetenskaper, Matematik

Göteborgs universitet

Discrete and Computational Geometry

0179-5376 (ISSN) 1432-0444 (eISSN)

Vol. 53 478-486

Styrkeområden

Informations- och kommunikationsteknik

Fundament

Grundläggande vetenskaper

Ämneskategorier

Diskret matematik

DOI

10.1007/s00454-014-9657-7