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 logoORCID: https://orcid.org/0000-0003-2964-7337, Clark, Ruaridh ORCID logoORCID: https://orcid.org/0000-0003-4601-2085 and Macdonald, Malcolm ORCID logoORCID: https://orcid.org/0000-0003-4499-4281; Cherifi, Hocine, Rocha, Luis M., Cherifi, Chantal and Donduran, Murat
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