A Connectivity-Sensitive Approach to Consensus Dynamics

Bernard Chazelle, Kritkorn Karntikoon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The paper resolves a long-standing open question in network dynamics. Averaging-based consensus has long been known to exhibit an exponential gap in relaxation time between the connected and disconnected cases, but a satisfactory explanation has remained elusive. We provide one by deriving nearly tight bounds on the s-energy of disconnected systems. This in turn allows us to relate the convergence rate of consensus dynamics to the number of connected components. We apply our results to opinion formation in social networks and provide a theoretical validation of the concept of an Overton window as an attracting manifold of “viable” opinions.

Original languageEnglish (US)
Title of host publication2nd Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2023
EditorsDavid Doty, Paul Spirakis
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959772754
DOIs
StatePublished - Jun 1 2023
Externally publishedYes
Event2nd Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2023 - Pisa, Italy
Duration: Jun 19 2023Jun 21 2023

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume257
ISSN (Print)1868-8969

Conference

Conference2nd Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2023
Country/TerritoryItaly
CityPisa
Period6/19/236/21/23

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • dynamic networks
  • multiagent systems
  • relaxation time
  • s-energy

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