A practical algorithm quantifies potential missing observations in IRL by computing minimal perturbations to recorded data that render expert actions optimal.
International Conference on Artificial Intelligence and Statistics , year=
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Quantifying Potential Observation Missingness in Inverse Reinforcement Learning
A practical algorithm quantifies potential missing observations in IRL by computing minimal perturbations to recorded data that render expert actions optimal.