83 citations · 125 across the 16 of their papers we have counts for
4 papers · 1 filter
Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning
Zifan Wu, Chao Yu, Chen Chen +2
In Model-based Reinforcement Learning (MBRL), model learning is critical since an inaccurate model can bias policy learning via generating misleading samples. However, learning an…
Text-Based Action-Model Acquisition for Planning
Kebing Jin, Huaixun Chen, Hankz Hankui Zhuo
Although there have been approaches that are capable of learning action models from plan traces, there is no work on learning action models from textual observations, which is perv…
Transfer Value Iteration Networks
Junyi Shen, Hankz Hankui Zhuo, Jin Xu +2
Value iteration networks (VINs) have been demonstrated to have a good generalization ability for reinforcement learning tasks across similar domains. However, based on our experime…
Federated Deep Reinforcement Learning
Hankz Hankui Zhuo, Wenfeng Feng, Yufeng Lin +2
In deep reinforcement learning, building policies of high-quality is challenging when the feature space of states is small and the training data is limited. Despite the success of…