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Probabilistic models as theories of children's minds

Published online by Cambridge University Press:  25 August 2011

Alison Gopnik
Alison Gopnik
Affiliation:
Department of Psychology, University of California at Berkeley, Berkeley, CA 94720. [email protected]
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Abstract

My research program proposes that children have representations and learning mechanisms that can be characterized as causal models of the world – coherent, structured hypotheses with consistent relationships to probabilistic patterns of evidence. We also propose that Bayesian inference is one mechanism by which children learn these models from data. These proposals are straightforward psychological hypotheses and far from “Bayesian Fundamentalism.”

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 4 , August 2011 , pp. 200 - 201
Copyright
Copyright © Cambridge University Press 2011

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References

Bonawitz, E. B., Ferranti, D., Saxe, R., Gopnik, A., Meltzoff, A. N., Woodward, J. & Schulz, L. E. (2010) Just do it? Investigating the gap between prediction and action in toddlers' causal inferences. Cognition 115(1):104–17.CrossRefGoogle Scholar
Buchsbaum, D., Griffiths, T. L. & Gopnik, A. (in press) Children's imitation of causal action sequences is influenced by statistical and pedagogical evidence. Cognition.Google Scholar
Danks, D. (2003) Equilibria of the Rescorla–Wagner model. Journal of Mathematical Psychology 47(2):109–21.CrossRefGoogle Scholar
Gopnik, A., Glymour, C., Sobel, D., Schulz, L., Kushnir, T. & Danks, D. (2004) A theory of causal learning in children: Causal maps and Bayes nets. Psychological Review 111(1):3–32.CrossRefGoogle ScholarPubMed
Gopnik, A. & Schulz, L., eds. (2007) Causal learning: Psychology, philosophy, and computation. Oxford University Press.CrossRefGoogle Scholar
Griffiths, T. L., Chater, N., Kemp, C., Perfors, A. & Tenenbaum, J. (2010) Probabilistic models of cognition: Exploring representations and inductive biases. Trends in Cognitive Sciences 14(8):357–64.CrossRefGoogle ScholarPubMed
Kushnir, T. & Gopnik, A. (2005) Young children infer causal strength from probabilities and interventions. Psychological Science 16(9):678–83.CrossRefGoogle ScholarPubMed
Kushnir, T. & Gopnik, A. (2007) Conditional probability versus spatial contiguity in causal learning: Preschoolers use new contingency evidence to overcome prior spatial assumptions. Developmental Psychology 43(1):186–96.CrossRefGoogle ScholarPubMed
Kushnir, T., Xu, F. & Wellman, H. (2010) Young children use statistical sampling to infer the preferences of others. Psychological Science 21:1134–40.CrossRefGoogle Scholar
Lucas, C., Gopnik, A. & Griffiths, T. (2010) Developmental differences in learning the form of causal relationships. In: Proceedings of the 32nd Annual Conference of the Cognitive Science Society, ed. Ohlsson, S. & Catrambone, R., pp. 2852–57. Cognitive Science Society.Google Scholar
Pearl, J. (2000) Causality: Models, reasoning, and inference. Cambridge University Press.Google Scholar
Schulz, L. E. & Bonawitz, E. B. (2007) Serious fun: Preschoolers engage in more exploratory play when evidence is confounded. Developmental Psychology 43:1045–50.CrossRefGoogle ScholarPubMed
Schulz, L. E., Bonawitz, E. B. & Griffiths, T. L. (2007a) Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers' causal inferences. Developmental Psychology 43(5):1124–39.CrossRefGoogle ScholarPubMed
Schulz, L. E, Gopnik, A. & Glymour, C. (2007b) Preschool children learn about causal structure from conditional interventions. Developmental Science 10(3):322–32.CrossRefGoogle ScholarPubMed
Schulz, L. E., Goodman, N. D., Tenenbaum, J. B. & Jenkins, A. C. (2008) Going beyond the evidence: Abstract laws and preschoolers' responses to anomalous data. Cognition 109(2):211–23.CrossRefGoogle ScholarPubMed
Sobel, D. M. & Kirkham, N. Z. (2006) Blickets and babies: The development of causal reasoning in toddlers and infants. Developmental Psychology 42(6):1103–15.CrossRefGoogle ScholarPubMed
Sobel, D. M., Tenenbaum, J. B. & Gopnik, A. (2004) Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers. Cognitive Science 28(3):303–33.Google Scholar
Spirtes, P., Glymour, C. & Scheines, R. (2000) Causation, prediction, and search, 2nd edition. (original edition published in 1993) MIT Press.Google Scholar