Inverse Reinforcement Learning with Missing Data

16 Nov 2019Tien MaiQuoc Phong NguyenKian Hsiang LowPatrick Jaillet

We consider the problem of recovering an expert's reward function with inverse reinforcement learning (IRL) when there are missing/incomplete state-action pairs or observations in the demonstrated trajectories. This issue of missing trajectory data or information occurs in many situations, e.g., GPS signals from vehicles moving on a road network are intermittent... (read more)

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