Tolerance-based disruption-tolerant consensus in directed networks
Bouis, Agathe and Lowe, Christopher and Clark, Ruaridh and Macdonald, Malcolm; Cherifi, Hocine and Rocha, Luis M. and Cherifi, Chantal and Donduran, Murat, eds. (2024) Tolerance-based disruption-tolerant consensus in directed networks. In: Complex Networks & Their Applications XII. Studies in Computational Intelligence, 4 . Springer, FRA, pp. 449-460. ISBN 9783031535031 (https://doi.org/10.1007/978-3-031-53503-1_37)
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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.
ORCID iDs
Bouis, Agathe, Lowe, Christopher ORCID: https://orcid.org/0000-0003-2964-7337, Clark, Ruaridh ORCID: https://orcid.org/0000-0003-4601-2085 and Macdonald, Malcolm ORCID: https://orcid.org/0000-0003-4499-4281; Cherifi, Hocine, Rocha, Luis M., Cherifi, Chantal and Donduran, Murat-
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Item type: Book Section ID code: 90287 Dates: DateEvent29 February 2024Published29 September 2023Accepted1 September 2023SubmittedNotes: Copyright © 2024 Springer-Verlag. This version of the paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at https://doi.org/10.1007/978-3-031-53503-1_37 Subjects: Technology > Electrical engineering. Electronics Nuclear engineering > Electrical apparatus and materials > Electric networks Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 19 Aug 2024 11:10 Last modified: 03 Oct 2024 09:50 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/90287