10 citations · 14 across the 4 of their papers we have counts for
4 papers
GraphRARE: Reinforcement Learning Enhanced Graph Neural Network with Relative Entropy
Tianhao Peng, Wenjun Wu, Haitao Yuan +6
Graph neural networks (GNNs) have shown advantages in graph-based analysis tasks. However, most existing methods have the homogeneity assumption and show poor performance on hetero…
ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning
Xin Yu, Rongye Shi, Pu Feng +3
Multi-agent reinforcement learning (MARL) has achieved promising results in recent years. However, most existing reinforcement learning methods require a large amount of data for m…
CLGT: A Graph Transformer for Student Performance Prediction in Collaborative Learning
Tianhao Peng, Yu Liang, Wenjun Wu +3
Modeling and predicting the performance of students in collaborative learning paradigms is an important task. Most of the research presented in literature regarding collaborative l…
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…