27 citations · 53 across the 5 of their papers we have counts for
5 papers
Normalization Enhances Generalization in Visual Reinforcement Learning
Lu Li, Jiafei Lyu, Guozheng Ma +4
Recent advances in visual reinforcement learning (RL) have led to impressive success in handling complex tasks. However, these methods have demonstrated limited generalization capa…
Uncertainty-driven Trajectory Truncation for Data Augmentation in Offline Reinforcement Learning
Junjie Zhang, Jiafei Lyu, Xiaoteng Ma +4
Equipped with the trained environmental dynamics, model-based offline reinforcement learning (RL) algorithms can often successfully learn good policies from fixed-sized datasets, e…
Mildly Conservative Q-Learning for Offline Reinforcement Learning
Jiafei Lyu, Xiaoteng Ma, Xiu Li +1
Offline reinforcement learning (RL) defines the task of learning from a static logged dataset without continually interacting with the environment. The distribution shift between t…
Reward function shape exploration in adversarial imitation learning: an empirical study
Yawei Wang, Xiu Li
For adversarial imitation learning algorithms (AILs), no true rewards are obtained from the environment for learning the strategy. However, the pseudo rewards based on the output o…
Wasserstein Distance guided Adversarial Imitation Learning with Reward Shape Exploration
Ming Zhang, Yawei Wang, Xiaoteng Ma +4
The generative adversarial imitation learning (GAIL) has provided an adversarial learning framework for imitating expert policy from demonstrations in high-dimensional continuous t…