Enhancing the Robustness of QMIX against State-adversarial Attacks

Deep reinforcement learning (DRL) performance is generally impacted by state-adversarial attacks, a perturbation applied to an agent's observation. Most recent research has concentrated on robust single-agent reinforcement learning (SARL) algorithms against state-adversarial attacks. Still, the...

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Veröffentlicht in:	arXiv.org 2023-07
Hauptverfasser:	Guo, Weiran, Liu, Guanjun, Zhou, Ziyuan, Wang, Ling, Wang, Jiacun
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Computer Science - Cryptography and Security Computer Science - Learning Computer Science - Multiagent Systems Deep learning Machine learning Multiagent systems Perturbation Robustness
Online-Zugang:	Volltext
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