Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learning

9 August 2021

Papers citing "Mis-spoke or mis-lead: Achieving Robustness in Multi-Agent Communicative Reinforcement Learning"

7 / 7 papers shown

Title
Heterogeneous Multi-agent Zero-Shot Coordination by Coevolution Ke Xue Yutong Wang Cong Guan Lei Yuan Haobo Fu Qiang Fu Chao Qian Yang Yu 40 16 0 03 Jan 2025
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning Maxwell Standen Junae Kim Claudia Szabo AAML 24 5 0 11 Jan 2023
Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems Yanchao Sun Ruijie Zheng Parisa Hassanzadeh Yongyuan Liang S. Feizi Sumitra Ganesh Furong Huang AAML 19 10 0 21 Jun 2022
Intelligent Blockchain-based Edge Computing via Deep Reinforcement Learning: Solutions and Challenges Dinh C. Nguyen Van-Dinh Nguyen Ming Ding Symeon Chatzinotas P. Pathirana Aruna Seneviratne O. Dobre Albert Y. Zomaya 6 10 0 17 Jun 2022
Trust-based Consensus in Multi-Agent Reinforcement Learning Systems Ho Long Fung Victor-Alexandru Darvariu Stephen Hailes Mirco Musolesi 17 5 0 25 May 2022
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary Huan Zhang Hongge Chen Duane S. Boning Cho-Jui Hsieh 59 161 0 21 Jan 2021
Adversarial Attacks On Multi-Agent Communication James Tu Tsun-Hsuan Wang Jingkang Wang S. Manivasagam Mengye Ren R. Urtasun AAML 71 46 0 17 Jan 2021