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Causal LearningPsychology, Philosophy, and Computation$
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Alison Gopnik and Laura Schulz

Print publication date: 2007

Print ISBN-13: 9780195176803

Published to Oxford Scholarship Online: April 2010

DOI: 10.1093/acprof:oso/9780195176803.001.0001

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Interactions Between Causal and Statistical Learning

Interactions Between Causal and Statistical Learning

(p.139) 9 Interactions Between Causal and Statistical Learning
Causal Learning

David M. Sobel

Natasha Z. Kirkham

Oxford University Press

Infants and young children appear to have powerful statistical learning mechanisms that allow them to acquire predictive information about the environment. Children also appear to possess powerful mechanisms for causal learning, which allow them not only to predict their environment, but to explain, interpret, and intervene. This chapter examines the relation between children's causal learning and inferential abilities, and their ability to recognize statistical regularity. It proposes that while there is more to causal learning than just statistical mechanisms, statistical learning abilities — particularly abilities that infants appear to possess — might help to lay the foundation for a mechanism for causal learning. It describes how the literature on infants' statistical learning has informed what we know about children's causal learning abilities.

Keywords:   causal learning, statistical learning, multimodal integration, children's causal inference

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