Competition-Based Resilience in Distributed Quadratic Optimization
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2022
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866915143429914624 |
|---|---|
| author | Ballotta, Luca Como, Giacomo Shamma, Jeff S. Schenato, Luca |
| author_facet | Ballotta, Luca Como, Giacomo Shamma, Jeff S. Schenato, Luca |
| contents | This paper proposes a novel approach to resilient distributed optimization with quadratic costs in a networked control system (e.g., wireless sensor network, power grid, robotic team) prone to external attacks (e.g., hacking, power outage) that cause agents to misbehave. Departing from classical filtering strategies proposed in literature, we draw inspiration from a game-theoretic formulation of the consensus problem and argue that adding competition to the mix can enhance resilience in the presence of malicious agents. Our intuition is corroborated by analytical and numerical results showing that i) our strategy highlights the presence of a nontrivial tradeoff between blind collaboration and full competition, and ii) such competition-based approach can outperform state-of-the-art algorithms based on Mean Subsequence Reduced. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2203_14099 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Competition-Based Resilience in Distributed Quadratic Optimization Ballotta, Luca Como, Giacomo Shamma, Jeff S. Schenato, Luca Systems and Control Multiagent Systems Optimization and Control 93B70 (Primary) 68M18, 93D09, 93D50 (Secondary) I.2.11 This paper proposes a novel approach to resilient distributed optimization with quadratic costs in a networked control system (e.g., wireless sensor network, power grid, robotic team) prone to external attacks (e.g., hacking, power outage) that cause agents to misbehave. Departing from classical filtering strategies proposed in literature, we draw inspiration from a game-theoretic formulation of the consensus problem and argue that adding competition to the mix can enhance resilience in the presence of malicious agents. Our intuition is corroborated by analytical and numerical results showing that i) our strategy highlights the presence of a nontrivial tradeoff between blind collaboration and full competition, and ii) such competition-based approach can outperform state-of-the-art algorithms based on Mean Subsequence Reduced. |
| title | Competition-Based Resilience in Distributed Quadratic Optimization |
| topic | Systems and Control Multiagent Systems Optimization and Control 93B70 (Primary) 68M18, 93D09, 93D50 (Secondary) I.2.11 |
| url | https://arxiv.org/abs/2203.14099 |