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Found 2 papers, 1 papers with code
Machine versus Human Attention in Deep Reinforcement Learning Tasks
1) How similar are the visual representations learned by RL agents and humans when performing the same task?
Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation
We focus on the task of learning from feedback, in which the human trainer not only gives binary evaluative "good" or "bad" feedback for queried state-action pairs, but also provides a visual explanation by annotating relevant features in images.
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