Bayesian validation of grammar productions for the language of thought

Probabilistic proposals of Language of Thoughts (LoTs) can explain learning across different domains as statistical inference over a compositionally structured hypothesis space. While frameworks may differ on how a LoT may be implemented computationally, they all share the property that they are bui...

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Detalles Bibliográficos
Autores principales:	Romano, S., Salles, A., Amalric, M., Dehaene, S., Sigman, M., Figueira, S.
Formato:	JOUR
Materias:	article geometry grammar human human experiment language probability scientist sequence learning theoretical study thinking validation process Bayes theorem cognition linguistics probability learning theoretical model Bayes Theorem Cognition Humans Linguistics Models, Theoretical Probability Learning Thinking
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_19326203_v13_n7_p_Romano
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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