A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.
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
Journal
Volume
111
Issue
1
Pages
3 - 32
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History