Adversarial attacks on cooperative multi-agent deep reinforcement learning: a dynamic group-based adversarial example transferability method

Adversarial attacks on cooperative multi-agent deep reinforcement learning: a dynamic group-based adversarial example transferability method

Abstract Existing research shows that cooperative multi-agent deep reinforcement learning (c-MADRL) is vulnerable to adversarial attacks, and c-MADRL is increasingly being applied to safety-critical domains. However, the robustness of c-MADRL against adversarial attacks has not been fully studied. I...

Full description

Bibliographic Details
Main Authors: Lixia Zan, Xiangbin Zhu, Zhao-Long Hu
Format: Article
Language:English
Published: Springer 2023-07-01
Series:Complex & Intelligent Systems
Subjects:
Multi-agent reinforcement learning
Adversarial attack
Dynamic grouping
Transfer attack
Attack efficiency
Online Access:https://doi.org/10.1007/s40747-023-01145-w

Internet

https://doi.org/10.1007/s40747-023-01145-w

Similar Items