8 citations · 14 across the 3 of their papers we have counts for
3 papers
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…
cs.LG2022★ 6 cited
Factored Adaptation for Non-Stationary Reinforcement Learning
Fan Feng, Biwei Huang, Kun Zhang +1
Dealing with non-stationarity in environments (e.g., in the transition dynamics) and objectives (e.g., in the reward functions) is a challenging problem that is crucial in real-wor…