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Learning task-agnostic representation via toddler-inspired learning
[article]
2021
arXiv
pre-print
One of the inherent limitations of current AI systems, stemming from the passive learning mechanisms (e.g., supervised learning), is that they perform well on labeled datasets but cannot deduce knowledge on their own. To tackle this problem, we derive inspiration from a highly intentional learning system via action: the toddler. Inspired by the toddler's learning procedure, we design an interactive agent that can learn and store task-agnostic visual representation while exploring and
arXiv:2101.11221v1
fatcat:d6fhxvc22fclvcmvkndpyqmgoq