S-MEDIRL, a deep inverse RL method with a bilateral filtering smoothing loss and demonstration extrapolation, learns to yield and avoid deadlock in a narrow crossing, reaching about 92% success.
An inverse reinforcement learning approach for customizing automated lane change systems,
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Learning Implicit Social Navigation Behavior using Deep Inverse Reinforcement Learning
S-MEDIRL, a deep inverse RL method with a bilateral filtering smoothing loss and demonstration extrapolation, learns to yield and avoid deadlock in a narrow crossing, reaching about 92% success.