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Causal Learning
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Causal Learning: Psychology, Philosophy, and Computation

Alison Gopnik and Laura Schulz

Abstract

This book outlines the recent revolutionary work in cognitive science formulating a “probabilistic model” theory of learning and development. It provides an accessible and clear introduction to the probabilistic modeling in psychology, including causal model, Bayes net, and Bayesian approaches. It also outlines new cognitive and developmental psychological studies of statistical and causal learning, imitation and theory-formation, new philosophical approaches to causation, and new computational approaches to the representation of intuitive concepts and theories. This book brings together resea ... More

Keywords: concepts, folk theories, cognitive development, Bayesian inference, causal models, causal knowledge, causal learning, probabilistic models, statistical learning, Bayes nets

Bibliographic Information

Print publication date: 2007 Print ISBN-13: 9780195176803
Published to Oxford Scholarship Online: April 2010 DOI:10.1093/acprof:oso/9780195176803.001.0001

Authors

Affiliations are at time of print publication.

Alison Gopnik, editor
University of California at Berkeley

Laura Schulz, editor
Brain and Cognitive Sciences, Massachusetts Institute of Technology