most citedCLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning

6 citations · 6 across the 1 of their papers we have counts for

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1 paper

cs.LG2023★ 6 cited

CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning

Sheng Yue, Guanbo Wang, Wei Shao +4

This work aims to tackle a major challenge in offline Inverse Reinforcement Learning (IRL), namely the reward extrapolation error, where the learned reward function may fail to exp…