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Multi-Agent Adversarial Attacks for Multi-Channel Communications. (arXiv:2201.09149v2 [cs.MA] UPDATED)
Jan. 28, 2022, 2:11 a.m. | Juncheng Dong, Suya Wu, Mohammadreza Sultani, Vahid Tarokh
cs.LG updates on arXiv.org arxiv.org
Recently Reinforcement Learning (RL) has been applied as an anti-adversarial
remedy in wireless communication networks. However, studying the RL-based
approaches from the adversary's perspective has received little attention.
Additionally, RL-based approaches in an anti-adversary or adversarial paradigm
mostly consider single-channel communication (either channel selection or
single channel power control), while multi-channel communication is more common
in practice. In this paper, we propose a multi-agent adversary system (MAAS)
for modeling and analyzing adversaries in a wireless communication scenario by
careful design …
More from arxiv.org / cs.LG updates on arXiv.org
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