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  1. The origin of concepts.Susan Carey - 2009 - New York: Oxford University Press.
    Only human beings have a rich conceptual repertoire with concepts like tort, entropy, Abelian group, mannerism, icon and deconstruction. How have humans constructed these concepts? And once they have been constructed by adults, how do children acquire them? While primarily focusing on the second question, in The Origin of Concepts , Susan Carey shows that the answers to both overlap substantially. Carey begins by characterizing the innate starting point for conceptual development, namely systems of core cognition. Representations of core cognition (...)
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  • A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.Alison Gopnik, Clark Glymour, Laura Schulz, Tamar Kushnir & David Danks - 2004 - Psychological Review 111 (1):3-32.
    We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children (...)
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  • Learning a theory of causality.Noah D. Goodman, Tomer D. Ullman & Joshua B. Tenenbaum - 2011 - Psychological Review 118 (1):110-119.
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  • Word learning as Bayesian inference.Fei Xu & Joshua B. Tenenbaum - 2007 - Psychological Review 114 (2):245-272.
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  • Going beyond the evidence: Abstract laws and preschoolers’ responses to anomalous data.Laura E. Schulz, Noah D. Goodman, Joshua B. Tenenbaum & Adrianna C. Jenkins - 2008 - Cognition 109 (2):211-223.
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  • Action experience alters 3-month-old infants' perception of others' actions.Jessica A. Sommerville, Amanda L. Woodward & Amy Needham - 2005 - Cognition 96 (1):B1-B11.
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  • (3 other versions)Causal learning in children: Causal maps and Bayes nets.Alison Gopnik, Clark Glymour, David M. Sobel & Laura E. Schultz - unknown
    We outline a cognitive and computational account of causal learning in children. We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent representation of the causal relations among events. This kind of knowledge can be perspicuously represented by the formalism of directed graphical causal models, or “Bayes nets”. Human causal learning and inference may involve computations similar to those for learnig causal Bayes nets and for predicting with (...)
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