4 citations · 11 across the 9 of their papers we have counts for
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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…