A theory of causal learning in children: causal maps and Bayes nets.

@article{Gopnik2004ATO,
  title={A theory of causal learning in children: causal maps and Bayes nets.},
  author={Alison Gopnik and Clark Glymour and David M. Sobel and Laura E. Schulz and Tamar Kushnir and David Danks},
  journal={Psychological review},
  year={2004},
  volume={111 1},
  pages={
          3-32
        }
}
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 causal learning and inference may involve computations… CONTINUE READING

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