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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Fading of collective attention shapes the evolution of linguistic variants ... Shalom, Diego E; Sigman, Mariano; Mindlin, Gabriel. - : arXiv, 2018 BASE Show details 2 Agreement attraction in Spanish comprehension ... Lago, Sol; Shalom, Diego; Sigman, Mariano. - : Open Science Framework, 2018 BASE Show details 3 The maturation of speech structure in psychosis is resistant to formal education Mota, Natália Bezerra; Sigman, Mariano; Cecchi, Guillermo. - : Nature Publishing Group UK, 2018 BASE Show details 4 Bayesian validation of grammar productions for the language of thought Romano, Sergio; Salles, Alejo; Amalric, Marie; Dehaene, Stanislas; Sigman, Mariano; Figueira, Santiago. - : Public Library of Science, 2018 Abstract: 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 built from a set of atomic symbols and rules by which these symbols can be combined. In this work we propose an extra validation step for the set of atomic productions defined by the experimenter. It starts by expanding the defined LoT grammar for the cognitive domain with a broader set of arbitrary productions and then uses Bayesian inference to prune the productions from the experimental data. The result allows the researcher to validate that the resulting grammar still matches the intuitive grammar chosen for the domain. We then test this method in the language of geometry, a specific LoT model for geometrical sequence learning. Finally, despite the fact of the geometrical LoT not being a universal (i.e. Turing-complete) language, we show an empirical relation between a sequence’s probability and its complexity consistent with the theoretical relationship for universal languages described by Levin’s Coding Theorem. Keyword: Research Article URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6039029/ http://www.ncbi.nlm.nih.gov/pubmed/29990351 https://doi.org/10.1371/journal.pone.0200420 BASE Hide details 5 Maintaining trust when agents can engage in self-deception Babino, Andrés; Makse, Hernán A.; DiTella, Rafael. - : National Academy of Sciences, 2018 BASE Show details 6 The maturation of speech structure in psychosis is resistant to formal education Mota, Natália Bezerra; Sigman, Mariano; Cecchi, Guillermo. - 2018 BASE Show details

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