24 citations · 27 across the 14 of their papers we have counts for
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cs.LG2023
CROP: Conservative Reward for Model-based Offline Policy Optimization
Hao Li, Xiao-Hu Zhou, Shu-Hai Li +6
Offline reinforcement learning (RL) aims to optimize a policy using collected data without online interactions. Model-based approaches are particularly appealing for addressing off…
cs.LG2023★ 1 cited
DOMAIN: MilDly COnservative Model-BAsed OfflINe Reinforcement Learning
Xiao-Yin Liu, Xiao-Hu Zhou, Mei-Jiang Gui +7
Model-based reinforcement learning (RL), which learns an environment model from the offline dataset and generates more out-of-distribution model data, has become an effective appro…