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Multi-Agent Adversarial Training Using Diffusion Learning

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arxiv 2303.01936 v1 pith:45WHSMBN submitted 2023-03-03 cs.LG cs.AIcs.MA

classification cs.LGcs.AIcs.MA
keywords adversariallearningdiffusionmulti-agenttraininganalyzeattacksconvergence
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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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