14 citations · 18 across the 2 of their papers we have counts for
5 papers
Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation
Zhizhou Ren, Anji Liu, Yitao Liang +2
Learning new task-specific skills from a few trials is a fundamental challenge for artificial intelligence. Meta reinforcement learning (meta-RL) tackles this problem by learning t…
Off-Policy Reinforcement Learning with Delayed Rewards
Beining Han, Zhizhou Ren, Zuofan Wu +2
We study deep reinforcement learning (RL) algorithms with delayed rewards. In many real-world tasks, instant rewards are often not readily accessible or even defined immediately af…
Generalizable Episodic Memory for Deep Reinforcement Learning
Hao Hu, Jianing Ye, Guangxiang Zhu +2
Episodic memory-based methods can rapidly latch onto past successful strategies by a non-parametric memory and improve sample efficiency of traditional reinforcement learning. Howe…
Exploration via Hindsight Goal Generation
Zhizhou Ren, Kefan Dong, Yuan Zhou +2
Goal-oriented reinforcement learning has recently been a practical framework for robotic manipulation tasks, in which an agent is required to reach a certain goal defined by a func…
Object-Oriented Dynamics Learning through Multi-Level Abstraction
Guangxiang Zhu, Jianhao Wang, Zhizhou Ren +2
Object-based approaches for learning action-conditioned dynamics has demonstrated promise for generalization and interpretability. However, existing approaches suffer from structur…