Symbolic metaprogram search improves learning efficiency and explains rule learning in humans
Throughout their lives, humans seem to learn a variety of rules for things like applying category labels, following procedures, and explaining causal relationships. These rules are often algorithmically rich but are nonetheless acquired with minimal data and computation. Symbolic models based on pro...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Nature Research
2024
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