4 citations · 11 across the 9 of their papers we have counts for
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cs.SI2023★ 1 cited
Adversarial Socialbots Modeling Based on Structural Information Principles
Xianghua Zeng, Hao Peng, Angsheng Li
The importance of effective detection is underscored by the fact that socialbots imitate human behavior to propagate misinformation, leading to an ongoing competition between socia…
cs.AI2023★ 3 cited
Hierarchical State Abstraction Based on Structural Information Principles
Xianghua Zeng, Hao Peng, Angsheng Li +3
State abstraction optimizes decision-making by ignoring irrelevant environmental information in reinforcement learning with rich observations. Nevertheless, recent approaches focus…
cs.AI2023★ 4 cited
Effective and Stable Role-Based Multi-Agent Collaboration by Structural Information Principles
Xianghua Zeng, Hao Peng, Angsheng Li
Role-based learning is a promising approach to improving the performance of Multi-Agent Reinforcement Learning (MARL). Nevertheless, without manual assistance, current role-based m…