AINeutralarXiv – CS AI · Jun 236/10
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Path-dependent program induction under resource constraints explains human sequence learning
Researchers developed a hierarchical Adaptor Grammar (HAG) model that explains how humans learn abstract patterns from sequential experiences under cognitive constraints. The framework combines rate-distortion theory with program induction to show that learning order influences which abstractions are discovered, with experimental validation from melodic sequence learning tasks demonstrating superior generalization and fit compared to alternative models.