Causal Learning: Psychology, Philosophy, and Computation by Alison GopnikCausal Learning: Psychology, Philosophy, and Computation by Alison Gopnik

Causal Learning: Psychology, Philosophy, and Computation

EditorAlison Gopnik, Laura Schulz

Hardcover | March 9, 2007

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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. During the last few years, there has been an interdisciplinaryrevolution in our understanding of learning and reasoning: Researchers in philosophy, psychology, and computation have discovered new mechanisms for learning the causal structure of the world. This new work provides a rigorous, formal basis for theory theories of concepts and cognitive development,and moreover, the causal learning mechanisms it has uncovered go dramatically beyond the traditional mechanisms of both nativist theories, such as modularity theories, and empiricist ones, such as association or connectionism.
Alison Gopnik is Professor of Psychology at the University of California at Berkeley. She is the coauthor of Words, Thoughts and Theories (1997), and The Scientist in the Crib (1999). She has written over a hundred scientific articles as well as articles for The New York Times, The New York Review of Books and Laura Schulz...
Title:Causal Learning: Psychology, Philosophy, and ComputationFormat:HardcoverDimensions:384 pages, 7.2 × 10 × 1.42 inPublished:March 9, 2007Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0195176804

ISBN - 13:9780195176803


Table of Contents

Introduction. Allison Gopnik and Laura Schulz: Part I. Causation and Intervention2. Andrew N. Meltzoff: Infants' Causal Learning: Intervention, Observation, Imitation3. Jessica A. Sommerville: Detecting Causal Structure: The Role of Intervention in Infants' Understanding of Psychological and Physical Causal Relations4. John Campbell: An Interventionist Approach to Causation in Psychology5. Laura Schulz, Tamar Kushnir, and Alison Gopnik: Learning From Doing: Intervention and Causal Inference6. York Hagmayer, Steven Sloman, David Lagnado, and Michael R. Waldmann: Casual Reasoning Through Intervention7. Christopher Hitchcock: On the Importance of Causal TaxonomyPart II: Causation and Probability. Introduction to Part II. Alison Gopnik and Laura Schulz: 8. Richard Scheines, Matt Easterday, and David Danks: Teaching the Normative Theory of Casual Reasoning9. David M. Sobel and Natasha Z. Kirkham: Interactions Between Causal and Statistical Learning10. David A. Lagnado, Michael R. Waldmann, York Hagmayer, and Steven A. Sloman: Beyond Covariation: Cues to Causal Structure11. David Danks: Theory Unification and Graphical Models in Human Categorization12. Bob Rehder: Essential as a Generative Theory of Classification13. Thomas Richardson, Laura Schultz, and Alison Gopnik: Data-mining Probabilists or Experimental Determinists?: A Dialogue on the Principles Underlying Causal Learning in Children14. Clark Glymour: Learning the Structure of Deterministic SystemsPart III: Causation, Theories and Mechanisms. Introduction to Part III. Alison Gopnik and Laura Schulz: 15. Michael Strevens: Why Represent Causal Relations?16. Henry M. Wellman and David Liu: Causal Reasoning as Informed by the Early Development of Explanations17. Woo-kyoung Ahn, Jessecae K. Marsh, and Christian C. Luhmann: Dynamic Interpretations of Covariation Data18. Clark Glymour: Statistical Jokes and Social Effects: Intervention and Invariance in Causal Relations19. Joshua B. Tenenbaum, Thomas L. Griffiths, and Sourabh Niyogi: Intuitive Theories as Grammars for Causal Inference20. Thomas L. Griffiths and Joshua B. Tenenbaum: Two Proposals for Causal GrammarsNotes. Index.

Editorial Reviews

"An exemplar of inter-disciplinary work: adventurous, coherent, readable, and even witty. A striking intervention into some often-encrusted literatures." --Peter Godfrey-Smith, Professor of Philosophy, Harvard University