Tolerance-based disruption-tolerant consensus in directed networks

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

Abstract

This article addresses the problem of resilient consensus for multi-agent networks. Resilience is used here to distinguish disruptive agents from compliant agents which follow a given control law. We present an algorithm enabling efficient and resilient network consensus based on an inversion of the social dynamics of the Deffuant model with emotions. This is achieved through the exploitation of a dynamic tolerance linked to extremism and clustering, whereby agents filter out extreme non-standard opinions driving them away from consensus. This method is not dependent on prior knowledge of either the network topology or the number of disruptive agents, making it suitable for real-world applications where this information is typically unavailable.
Original languageEnglish
Title of host publicationComplex Networks & Their Applications XII
Subtitle of host publicationProceedings of The Twelfth International Conference on Complex Networks and their Applications: COMPLEX NETWORKS 2023
EditorsHocine Cherifi, Luis M. Rocha, Chantal Cherifi, Murat Donduran
Place of PublicationCham
PublisherSpringer
Pages449-460
Number of pages12
Volume4
ISBN (Electronic)9783031535031
ISBN (Print)9783031535024
DOIs
Publication statusPublished - 29 Feb 2024
EventComplex Networks 2023 - Menton Riviera, France
Duration: 28 Nov 202330 Nov 2023

Publication series

NameStudies in Computational Intelligence
Volume1144
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

Conference

ConferenceComplex Networks 2023
Country/TerritoryFrance
CityMenton Riviera
Period28/11/2330/11/23

Keywords

  • consensus algorithm
  • fault tolerance
  • social dynamics

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