Causal Learning: Psychology, Philosophy, and Computation: Oxford Series in Cognitive Development
Editat de Alison Gopnik, Laura Schulzen Limba Engleză Hardback – 26 apr 2007
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Specificații
ISBN-13: 9780195176803
ISBN-10: 0195176804
Pagini: 384
Ilustrații: 108 line illustrations, 10 black and white photographs, 8 shaded line illustrations
Dimensiuni: 254 x 183 x 36 mm
Greutate: 0.82 kg
Editura: Oxford University Press
Colecția OUP USA
Seria Oxford Series in Cognitive Development
Locul publicării:New York, United States
ISBN-10: 0195176804
Pagini: 384
Ilustrații: 108 line illustrations, 10 black and white photographs, 8 shaded line illustrations
Dimensiuni: 254 x 183 x 36 mm
Greutate: 0.82 kg
Editura: Oxford University Press
Colecția OUP USA
Seria Oxford Series in Cognitive Development
Locul publicării:New York, United States
Recenzii
...well worth the effort of reading...a well-developed overview of the current state of research in the field of causal learning.
Cuprins
- Part I: Causation and Intervention
- 1: Interventionist Theories of Causation in Psychological Perspective
- 2: Infants' Causal Learning: Intervention, Observation, Imitation
- 3: Detecting Causal Structure: The Role of Interventions in Infants' Understanding of Psychological and Physical Causal Relations
- 4: An Interventionist Approach to Causation in Psychology
- 5: Learning From Doing: Intervention and Causal Inference
- 6: Causal Reasoning Through Intervention
- 7: On the Importance of Causal Taxonomy
- Part II: Causation and Probability
- Introduction to Part II: Causation and Probability
- 8: Teaching the Normative Theory of Causal Reasoning
- 9: Interactions Between Causal and Statistical Learning
- 10: Beyond Covariation: Cues to Causal Structure
- 11: Theory Unification and Graphical Models in Human Categorization
- 12: Essentialism as a Generative Theory of Classification
- 13: Data-Mining Probalists or Experimental Determinists? A Dialogue on the Principles Underlying Causal Learning in Children
- 14: Learning the Structure of Deterministic Systems
- Part III: Causation, Theories, and Mechanisms
- Introduction to Part III: Causation, Theories, and Mechanisms
- 15: Why Represent Causal Relations?
- 16: Causal Reasoning as Informed by the Early Development of Explanations
- 17: Dynamic Interpretations of Covariation Data
- 18: Statistical Jokes and Social Effects: Intervention and Invariance in Causal Relations
- 19: Intuitive Theories as Grammars for Causal Inference
- 20: Two Proposals for Causal Grammars