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arXiv · 2402.05744

Learning Families of Algebraic Structures from Text

Nikolay Bazhenov·Ekaterina Fokina·Dino Rossegger·Alexandra Soskova·Stefan Vatev
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Abstract

We adapt the classical notion of learning from text to computable structure theory. Our main result is a model-theoretic characterization of the learnability from text for classes of structures. We show that a family of structures is learnable from text if and only if the structures can be distinguished in terms of their theories restricted to positive infinitary $\Sigma_2$ sentences.

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Nikolay Bazhenov, Ekaterina Fokina, Dino Rossegger, Alexandra Soskova, Stefan Vatev. 2024-02-08. Learning Families of Algebraic Structures from Text. https://arxiv.org/abs/2402.05744

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