8 citations · 10 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 2 cited
Learning World Models with Identifiable Factorization
Yu-Ren Liu, Biwei Huang, Zhengmao Zhu +4
Extracting a stable and compact representation of the environment is crucial for efficient reinforcement learning in high-dimensional, noisy, and non-stationary environments. Diffe…
cs.LG2023
Beware of Instantaneous Dependence in Reinforcement Learning
Zhengmao Zhu, Yuren Liu, Honglong Tian +2
Playing an important role in Model-Based Reinforcement Learning (MBRL), environment models aim to predict future states based on the past. Existing works usually ignore instantaneo…
cs.LG2022★ 8 cited
Offline Reinforcement Learning with Causal Structured World Models
Zheng-Mao Zhu, Xiong-Hui Chen, Hong-Long Tian +2
Model-based methods have recently shown promising for offline reinforcement learning (RL), aiming to learn good policies from historical data without interacting with the environme…