We investigate a novel approach to resilient distributed optimization with quadratic costs in a multiagent system prone to unexpected events that make some agents misbehave. In contrast to commonly adopted filtering strategies, we draw inspiration from phenomena modeled through the Friedkin-Johnsen dynamics and argue that adding competition to the mix can improve resilience in the presence of misbehaving agents. Our intuition is corroborated by analytical and numerical results showing that (i) there exists a nontrivial trade-off between full collaboration and full competition and (ii) our competition-based approach can outperform state-of-the-art algorithms based on Weighted Mean Subsequence Reduced. We also study impact of communication topology and connectivity on resilience, pointing out insights to robust network design.

Can Competition Outperform Collaboration? the Role of Misbehaving Agents / Ballotta, Luca; Como, Giacomo; Shamma, Jeff S.; Schenato, Luca. - In: IEEE TRANSACTIONS ON AUTOMATIC CONTROL. - ISSN 0018-9286. - 69:4(2024), pp. 2308-2323. [10.1109/TAC.2023.3329850]

Can Competition Outperform Collaboration? the Role of Misbehaving Agents

Giacomo Como;Luca Schenato
2024

Abstract

We investigate a novel approach to resilient distributed optimization with quadratic costs in a multiagent system prone to unexpected events that make some agents misbehave. In contrast to commonly adopted filtering strategies, we draw inspiration from phenomena modeled through the Friedkin-Johnsen dynamics and argue that adding competition to the mix can improve resilience in the presence of misbehaving agents. Our intuition is corroborated by analytical and numerical results showing that (i) there exists a nontrivial trade-off between full collaboration and full competition and (ii) our competition-based approach can outperform state-of-the-art algorithms based on Weighted Mean Subsequence Reduced. We also study impact of communication topology and connectivity on resilience, pointing out insights to robust network design.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2983684