SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent
Reinforcement Learning

SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning

11 January 2023

Maxwell Standen

Papers citing "SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning"

9 / 9 papers shown

Title
A Novel Bifurcation Method for Observation Perturbation Attacks on Reinforcement Learning Agents: Load Altering Attacks on a Cyber Physical Power System Kiernan Broda-Milian Ranwa Al-Mallah H. Dagdougui AAML 40 0 0 06 Jul 2024
Learning Cyber Defence Tactics from Scratch with Multi-Agent Reinforcement Learning Jacob Wiebe Ranwa Al Mallah Li Li AAML 36 3 0 25 Aug 2023
Beyond Robustness: A Taxonomy of Approaches towards Resilient Multi-Robot Systems Amanda Prorok Matthew Malencia Luca Carlone Gaurav Sukhatme Brian M. Sadler Vijay Kumar 97 53 0 25 Sep 2021
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 35 0 09 Aug 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 82 475 0 02 Feb 2021
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
On the Robustness of Cooperative Multi-Agent Reinforcement Learning Jieyu Lin Kristina Dzeparoska S. Zhang A. Leon-Garcia Nicolas Papernot AAML 69 65 0 08 Mar 2020
Challenges and Countermeasures for Adversarial Attacks on Deep Reinforcement Learning Inaam Ilahi Muhammad Usama Junaid Qadir M. Janjua Ala I. Al-Fuqaha D. Hoang Dusit Niyato AAML 59 132 0 27 Jan 2020
Robust Deep Reinforcement Learning for Security and Safety in Autonomous Vehicle Systems A. Ferdowsi Ursula Challita Walid Saad N. Mandayam AAML 49 94 0 02 May 2018