A truthful mechanism design for distributed optimisation algorithms in networks with self-interested agents☆
File(s)
Published version
Author(s)
Zhong, Tianyi
Angeli, David
Type
Journal Article
Abstract
Enhancing resilience in multi-agent systems in the face of selfish agents is an important problem that requires further characterisation. This work develops a truthful mechanism that avoids self-interested and strategic agents maliciously manipulating the algorithm. We prove theoretically that the proposed mechanism incentivises self-interested agents to participate and follow the provided algorithm faithfully. Additionally, the mechanism is compatible with any distributed optimisation algorithm that can calculate at least one subgradient at a given point. Finally, we present an illustrative example that shows the effectiveness of the mechanism.
Date Issued
2026-02-01
Date Acceptance
2025-10-27
Citation
Automatica, 2026, 184
ISSN
0005-1098
Publisher
Elsevier
Journal / Book Title
Automatica
Volume
184
Copyright Statement
© 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Subjects
ALLOCATION
Automation & Control Systems
Distributed optimisation
Engineering
Engineering, Electrical & Electronic
Incentive mechanism design
Multi-agent system
Science & Technology
Technology
Publication Status
Published
Article Number
112727
Date Publish Online
2025-12-12