2 papers
cs.LG2025
Sample-Efficient Policy Constraint Offline Deep Reinforcement Learning based on Sample Filtering
Yuanhao Chen, Qi Liu, Pengbin Chen +2
Offline reinforcement learning (RL) aims to learn a policy that maximizes the expected return using a given static dataset of transitions. However, offline RL faces the distributio…
cs.LG2024
SUMO: Search-Based Uncertainty Estimation for Model-Based Offline Reinforcement Learning
Zhongjian Qiao, Jiafei Lyu, Kechen Jiao +2
The performance of offline reinforcement learning (RL) suffers from the limited size and quality of static datasets. Model-based offline RL addresses this issue by generating synth…