Multi-Agent Adversarial Training Using Diffusion Learning

• URL: http://arxiv.org/abs/2303.01936v1
• Date: Fri, 3 Mar 2023 14:05:59 GMT
• Title: Multi-Agent Adversarial Training Using Diffusion Learning
• Authors: Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed
• Abstract summary: We propose a general adversarial training framework for multi-agent systems using diffusion learning. We analyze the convergence properties of the proposed scheme for convex optimization problems, and illustrate its enhanced robustness to adversarial attacks.
• Score: 55.28669771020857
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This work focuses on adversarial learning over graphs. We propose a general adversarial training framework for multi-agent systems using diffusion learning. We analyze the convergence properties of the proposed scheme for convex optimization problems, and illustrate its enhanced robustness to adversarial attacks.

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