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Certifiably Robust Policy Learning against Adversarial Communication in
  Multi-agent Systems

Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems

21 June 2022
Yanchao Sun
Ruijie Zheng
Parisa Hassanzadeh
Yongyuan Liang
S. Feizi
Sumitra Ganesh
Furong Huang
    AAML
ArXivPDFHTML

Papers citing "Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems"

4 / 4 papers shown
Title
What is the Solution for State-Adversarial Multi-Agent Reinforcement
  Learning?
What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
Songyang Han
Sanbao Su
Sihong He
Shuo Han
Haizhao Yang
Shaofeng Zou
Fei Miao
AAML
25
22
0
06 Dec 2022
Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative
  Reinforcement Learning
Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learning
Wanqi Xue
Wei Qiu
Bo An
Zinovi Rabinovich
S. Obraztsova
C. Yeo
AAML
45
34
0
09 Aug 2021
Robust Reinforcement Learning on State Observations with Learned Optimal
  Adversary
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary
Huan Zhang
Hongge Chen
Duane S. Boning
Cho-Jui Hsieh
64
162
0
21 Jan 2021
Adversarial Attacks On Multi-Agent Communication
Adversarial Attacks On Multi-Agent Communication
James Tu
Tsun-Hsuan Wang
Jingkang Wang
S. Manivasagam
Mengye Ren
R. Urtasun
AAML
85
59
0
17 Jan 2021
1