13 found
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  1.  18
    Causal Learning Mechanisms in Very Young Children: Two-, Three-, and Four-Year-Olds Infer Causal Relations From Patterns of Variation and Covariation.Clark Glymour, Alison Gopnik, David M. Sobel & Laura E. Schulz - unknown
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  2.  9
    Young Children Are Reality-Prone When Thinking About Stories.Deena Skolnick Weisberg, Paul Bloom, David M. Sobel & Joshua Goodstein - 2013 - Journal of Cognition and Culture 13 (3-4):383-407.
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  3.  6
    Knowledge Matters: How Children Evaluate the Reliability of Testimony as a Process of Rational Inference.David M. Sobel & Tamar Kushnir - 2013 - Psychological Review 120 (4):779-797.
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  4.  61
    Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults.Thomas L. Griffiths, David M. Sobel, Joshua B. Tenenbaum & Alison Gopnik - 2011 - Cognitive Science 35 (8):1407-1455.
    People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which (...)
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  5. 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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  6.  4
    Of Blickets, Butterflies, and Baby Dinosaurs: Children’s Diagnostic Reasoning Across Domains.Deena Skolnick Weisberg, Elysia Choi & David M. Sobel - 2020 - Frontiers in Psychology 11.
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  7.  8
    Interactions Between Causal and Statistical Learning.David M. Sobel & Natasha Z. Kirkham - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation. Oxford University Press. pp. 139--153.
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  8.  14
    Enabling Conditions and Children’s Understanding of Pretense.David M. Sobel - 2009 - Cognition 113 (2):177-188.
  9.  9
    Reach Tracking Reveals Dissociable Processes Underlying Cognitive Control.Christopher D. Erb, Jeff Moher, David M. Sobel & Joo-Hyun Song - 2016 - Cognition 152:114-126.
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  10.  8
    Children’s Developing Understanding of the Relation Between Variable Causal Efficacy and Mechanistic Complexity.Christopher D. Erb, David W. Buchanan & David M. Sobel - 2013 - Cognition 129 (3):494-500.
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  11.  7
    Cognitive Control in Action: Tracking the Dynamics of Rule Switching in 5- to 8-Year-Olds and Adults.Christopher D. Erb, Jeff Moher, Joo-Hyun Song & David M. Sobel - 2017 - Cognition 164:163-173.
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  12.  3
    Bridging the Gap: Children's Developing Inferences About Objects' Labels and Insides From Causality-at-a-Distance.David W. Buchanan & David M. Sobel - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 64--70.
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  13.  3
    Knowledge and Children's Reasoning About Possibility.David M. Sobel - 2011 - In Christoph Hoerl, Teresa McCormack & Sarah R. Beck (eds.), Understanding Counterfactuals, Understanding Causation. Oxford University Press. pp. 123.
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