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Learning to See through Action: Predictive Curiosity for Robots

Zarifis, Stelios et al.
arXiv (All) · Papers
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machine-learningrobotics
Humans and animals do not learn vision from a fixed set of data: they move, interact, and learn from the visual consequences of their actions. Motivated by this developmental view, we study whether robots can improve visual learning by actively collecting experience through curiosity-driven interact
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