Book

Causal Learning

Edited by Alison Gopnik and Laura Schulz

Published in print April 2007 | ISBN: 9780195176803
Published online April 2010 | e-ISBN: 9780199958511 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780195176803.001.0001

Series: Oxford Series in Cognitive Development

Causal Learning

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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 research in all of these areas of cognitive science, with chapters by researchers in all these disciplines. Understanding causal structure is a central task of human cognition. Causal learning underpins the development of our concepts and categories, our intuitive theories, and our capacities for planning, imagination, and inference. This new work uses the framework of probabilistic models and interventionist accounts of causation in philosophy in order to provide a rigorous formal basis for “theory theories” of concepts and cognitive development. Moreover, the causal learning mechanisms this interdisciplinary research program has uncovered go dramatically beyond both the traditional mechanisms of nativist theories such as modularity theories, and empiricist ones such as association or connectionism. The chapters cover three topics: the role of intervention and action in causal understanding, the role of causation in categories and concepts, and the relationship between causal learning and intuitive theory formation. Though coming from different disciplines, the chapters converge on showing how we can use our own actions and the evidence we observe in order to accurately learn about the world.

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

Book.  358 pages.  Illustrated.

Subjects: Developmental Psychology

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Table of Contents

Introduction in Causal Learning

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Learning From Doing in Causal Learning

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