A Theory of Causal Learning in Children: Causal Maps and Bayes Nets

Psychological Review 111 (1):3-32 (2004)
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Abstract

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 construct new causal maps and that their learning is consistent with the Bayes net formalism.

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Author Profiles

David Danks
University of California, San Diego
Alison Gopnik
University of California, Berkeley

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Nature's Capacities and Their Measurement.Nancy Cartwright - 1989 - Oxford, England: Oxford University Press.
The Direction of Time.Hans Reichenbach - 1956 - Dover Publications.
A Treatise of Human Nature.David Hume & A. D. Lindsay - 1958 - Philosophical Quarterly 8 (33):379-380.

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