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

Volume: 111, Issue: 1, Pages: 3 - 32
Published: Jan 1, 2004
Abstract
The authors outline a cognitive and computational account of causal learning in children. They propose that children use 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...
Paper Details
Title
A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.
Published Date
Jan 1, 2004
Volume
111
Issue
1
Pages
3 - 32
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