most citedAttacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence

3 citations · 6 across the 3 of their papers we have counts for

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cs.LG2024★ 3 cited

Deep Graph Anomaly Detection: A Survey and New Perspectives

Hezhe Qiao, Hanghang Tong, Bo An +3

Graph anomaly detection (GAD), which aims to identify unusual graph instances (nodes, edges, subgraphs, or graphs), has attracted increasing attention in recent years due to its si…

cs.LG2023★ 3 cited

Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence

Simin Li, Jun Guo, Jingqiao Xiu +8

This study probes the vulnerabilities of cooperative multi-agent reinforcement learning (c-MARL) under adversarial attacks, a critical determinant of c-MARL's worst-case performanc…