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[null,"1.","Record Nr.",null,"UNINA9910974248003321"]
[null,null,"Titolo",null,"Causal learning : psychology, philosophy, and computation / / edited by Alison Gopnik, Laura Schulz"]
[null,null,"Pubbl/distr/stampa",null,"Oxford ; ; New York, : Oxford University Press, 2007"]
[null,null,"ISBN",null,"9780198039280"]
[{"$nulls":4},"019803928X"]
[{"$nulls":4},"978019517680"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource"]
[null,null,"Collana",null,"Oxford Series in Cognitive Development"]
[null,null,"Disciplina",null,"153.1/5"]
[null,null,"Soggetti",null,"Learning, Psychology of"]
[{"$nulls":4},"Causation"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Introduction. Allison Gopnik and Laura Schulz. 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 ..."]
[null,null,null,"Sommario/riassunto","Casual Learning provides a compendium of research determining how, in principle, the problem of causal inference and learning can be solved, and a wealth of methods for determining how it is, in fact, solved by children, adults, and animals.This is the first book to bring together leading researchers carrying out this new research in all these areas of cognitive science. The chapters focus on 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. The book provides an accessible and clear introduction to the new computational ideas, and with many coauthored chapters and much interaction between the chapters, it presents an active dialogue among the authors."]