The logical primitives of thought: Empirical foundations for compositional cognitive models.

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  • Additional Information
    • Source:
      Publisher: American Psychological Association Country of Publication: United States NLM ID: 0376476 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1939-1471 (Electronic) Linking ISSN: 0033295X NLM ISO Abbreviation: Psychol Rev Subsets: MEDLINE
    • Publication Information:
      Original Publication: Washington, DC : American Psychological Association
    • Subject Terms:
      Cognition* ; Concept Formation* ; Language* ; Learning* ; Thinking*; Bayes Theorem ; Humans ; Logic ; Models, Psychological
    • Abstract:
      The notion of a compositional language of thought (LOT) has been central in computational accounts of cognition from earliest attempts (Boole, 1854; Fodor, 1975) to the present day (Feldman, 2000; Penn, Holyoak, & Povinelli, 2008; Fodor, 2008; Kemp, 2012; Goodman, Tenenbaum, & Gerstenberg, 2015). Recent modeling work shows how statistical inferences over compositionally structured hypothesis spaces might explain learning and development across a variety of domains. However, the primitive components of such representations are typically assumed a priori by modelers and theoreticians rather than determined empirically. We show how different sets of LOT primitives, embedded in a psychologically realistic approximate Bayesian inference framework, systematically predict distinct learning curves in rule-based concept learning experiments. We use this feature of LOT models to design a set of large-scale concept learning experiments that can determine the most likely primitives for psychological concepts involving Boolean connectives and quantification. Subjects' inferences are most consistent with a rich (nonminimal) set of Boolean operations, including first-order, but not second-order, quantification. Our results more generally show how specific LOT theories can be distinguished empirically. (PsycINFO Database Record
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    • Grant Information:
      F32 HD070544 United States HD NICHD NIH HHS
    • Publication Date:
      Date Created: 20160415 Date Completed: 20170718 Latest Revision: 20180510
    • Publication Date:
      20240628
    • Accession Number:
      10.1037/a0039980
    • Accession Number:
      27077241