Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
Structural Information-based Hierarchical Diffusion for Offline Reinforcement Learning
Xianghua Zeng, Hao Peng, Angsheng Li +1
Diffusion-based generative methods have shown promising potential for modeling trajectories from offline reinforcement learning (RL) datasets, and hierarchical diffusion has been i…
cs.LG2024
Effective Exploration Based on the Structural Information Principles
Xianghua Zeng, Hao Peng, Angsheng Li
Traditional information theory provides a valuable foundation for Reinforcement Learning, particularly through representation learning and entropy maximization for agent exploratio…