Multi-Agent Adversarial Training Using Diffusion Learning

Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed
3/3/2023
cs.LGcs.AIcs.MA

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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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Cite this paper

@article{cao2023multiagent,
  title  = {Multi-Agent Adversarial Training Using Diffusion Learning},
  author = {Ying Cao and Elsa Rizk and Stefan Vlaski and Ali H. Sayed},
  year   = {2023},
  eprint = {2303.01936},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.01936v1}
}

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