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A unified account of abstract structure and conceptual change: Probabilistic models and early learning mechanisms

Published online by Cambridge University Press:  19 May 2011

Alison Gopnik
Alison Gopnik
Affiliation:
Department of Psychology, University of California at Berkeley, Berkeley, CA 94720. gopnik@berkeley.eduwww.alisongopnik.com
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Abstract

We need not propose, as Carey does, a radical discontinuity between core cognition, which is responsible for abstract structure, and language and “Quinian bootstrapping,” which are responsible for learning and conceptual change. From a probabilistic models view, conceptual structure and learning reflect the same principles, and they are both in place from the beginning.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 3 , June 2011 , pp. 129 - 130
Copyright
Copyright © Cambridge University Press 2011

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References

Carey, S. (2009) The origin of concepts. Oxford University Press.CrossRefGoogle Scholar
Goodman, N. D., Ullman, T. D. & Tenenbaum, J. B. (2011) Learning a theory of causality. Psychological Review 118(1):110–19.CrossRefGoogle ScholarPubMed
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):1–32.CrossRefGoogle ScholarPubMed
Gopnik, A. & Schulz, L., eds. (2007) Causal learning: Philosophy, psychology and computation. Oxford University Press.CrossRefGoogle Scholar
Graf Estes, K., Alibali, M. W., Evans, J. L. & Saffran, J. R. (2007) Can infants map meaning to newly segmented words? Statistical segmentation and word learning. Psychological Science 18(3):254–60.CrossRefGoogle ScholarPubMed
Griffiths, T., 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
Inagaki, K. & Hatano, G. (2004) Vitalistic causality in young children's naïve biology. Trends in Cognitive Sciences 8(8):356–62.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
Lany, J. & Saffran, J. (2010) From statistics to meaning: Infants' acquisition of lexical categories. Psychological Science 21(2):284–91.CrossRefGoogle ScholarPubMed
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
Meltzoff, A. & Brooks, R. (2008) Self-experience as a mechanism for learning about others. Developmental Psychology 44(5):1257–65.CrossRefGoogle ScholarPubMed
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., Goodman, N., Tenenbaum, J. & Jenkins, A. (2008) Going beyond the evidence: Abstract laws and preschoolers' responses to anomalous data. Cognition 109(2):211–23.CrossRefGoogle ScholarPubMed
Seiver, E., Gopnik, A. & Goodman, N. (under review) Did she jump because she was brave or because the trampoline was safe? Causal inference and the development of social cognition.Google Scholar
Somerville, J., Woodward, A. & Needham, A. (2005) Action experience alters 3-month-old infants' perception of others' actions. Cognition 96:1–11.CrossRefGoogle Scholar
Tenenbaum, J., Griffiths, T. & Nioyogi, S. (2007) Intuitive theories as grammars for causal inference. In: Causal learning: Philosophy, psychology and computation, ed. Gopnik, A. & Schulz, L., Oxford University Press.Google Scholar
Wang, S. & Baillargeon, R. (2008) Can infants be “taught” to attend to a new physical variable in an event category? The case of height in covering events. Cognitive Psychology 56(4):284–326.CrossRefGoogle Scholar
Wellman, H. & Liu, D. (2007) Causal reasoning as informed by the early development of explanations. In: Causal learning: Philosophy, psychology and computation, ed. Gopnik, A. & Schulz, L., pp. 261–79. Oxford University Press.CrossRefGoogle Scholar
Woodward, A. & Needham, A. (2009) Learning and the infant mind. Oxford University Press.Google Scholar
Xu, F. & Tenenbaum, J. B. (2007) Word learning as Bayesian inference. Psychological Review 114:245–72.CrossRefGoogle ScholarPubMed