3 papers
cs.LG2025
Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
Qingmao Yao, Zhichao Lei, Tianyuan Chen +5
Offline Reinforcement Learning (RL) struggles with distributional shifts, leading to the -value overestimation for out-of-distribution (OOD) actions. Existing methods address th…
cs.LG2024
Preference-Guided Reinforcement Learning for Efficient Exploration
Guojian Wang, Jianxiang Liu, Xinyuan Li +4
In this paper, we investigate preference-based reinforcement learning (PbRL), which enables reinforcement learning (RL) agents to learn from human feedback. This is particularly va…
cs.LG2024
Policy Optimization with Smooth Guidance Learned from State-Only Demonstrations
Guojian Wang, Faguo Wu, Xiao Zhang +1
The sparsity of reward feedback remains a challenging problem in online deep reinforcement learning (DRL). Previous approaches have utilized offline demonstrations to achieve impre…