Part I. Causation and Intervention

1. Interventionist Theories of Causation in Psychological Perspective, Jim Woodward

2. Infants' Causal Learning: Intervention, Observation, Imitation, Andrew N. Meltzoff

3. Detecting Causal Structure: The Role of Intervention in Infants' Understanding of Psychological and Physical Causal Relations, Jessica A. Sommerville

4. An Interventionist Approach to Causation in Psychology, John Campbell

5. Learning From Doing: Intervention and Causal Inference, Laura Schulz, Tamar Kushnir, and Alison Gopnik

6. Casual Reasoning Through Intervention, York Hagmayer, Steven Sloman, David Lagnado, and Michael R. Waldmann

7. On the Importance of Causal Taxonomy, Christopher Hitchcock

Part II: Causation and Probability.

Introduction to Part II. Alison Gopnik and Laura Schulz

8. Teaching the Normative Theory of Casual Reasoning, Richard Scheines, Matt Easterday, and David Danks

9. Interactions Between Causal and Statistical Learning, David M. Sobel and Natasha Z. Kirkham

10. Beyond Covariation: Cues to Causal Structure, David A. Lagnado, Michael R. Waldmann, York Hagmayer, and Steven A. Sloman

11. Theory Unification and Graphical Models in Human Categorization, David Danks

12. Essential as a Generative Theory of Classification, Bob Rehder

13. Data-mining Probabilists or Experimental Determinists?: A Dialogue on the Principles Underlying Causal Learning in Children, Thomas Richardson, Laura Schultz, and Alison Gopnik

14. Learning the Structure of Deterministic Systems, Clark Glymour

Part III: Causation, Theories and Mechanisms.

Introduction to Part III. Alison Gopnik and Laura Schulz

15. Why Represent Causal Relations?, Michael Strevens

16. Causal Reasoning as Informed by the Early Development of Explanations, Henry M. Wellman and David Liu

17. Dynamic Interpretations of Covariation Data, Woo-kyoung Ahn, Jessecae K. Marsh, and Christian C. Luhmann

18. Statistical Jokes and Social Effects: Intervention and Invariance in Causal Relations, Clark Glymour

19. Intuitive Theories as Grammars for Causal Inference, Joshua B. Tenenbaum, Thomas L. Griffiths, and Sourabh Niyogi

20. Two Proposals for Causal Grammars, Thomas L. Griffiths and Joshua B. Tenenbaum

Notes.

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