Causal Learning: Psychology, Philosophy, and ComputationAlison Gopnik, Laura Schulz 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 interdisciplinary revolution 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. |
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Page vii
... Infants ' Causal Learning : Intervention , Observation , Imitation 37 Andrew N. Meltzoff 3 Detecting Causal Structure : The Role of Interventions in Infants ' Understanding of Psychological and Physical Causal Relations Jessica A ...
... Infants ' Causal Learning : Intervention , Observation , Imitation 37 Andrew N. Meltzoff 3 Detecting Causal Structure : The Role of Interventions in Infants ' Understanding of Psychological and Physical Causal Relations Jessica A ...
Page 9
... infants and young children— considerable research has suggested that Piaget underestimated the causal reasoning abilities of young children. Both infants and adults seem to per- ceive causality when objects (like billiard balls) col ...
... infants and young children— considerable research has suggested that Piaget underestimated the causal reasoning abilities of young children. Both infants and adults seem to per- ceive causality when objects (like billiard balls) col ...
Page 10
... infants who learn , for instance , that kicking makes a mobile spin , will both repeat the behavior and remember it after significant delays ( Rovee - Collier , 1980 ; Watson & Ramey , 1972 ) . Instrumental learning — the ability to ...
... infants who learn , for instance , that kicking makes a mobile spin , will both repeat the behavior and remember it after significant delays ( Rovee - Collier , 1980 ; Watson & Ramey , 1972 ) . Instrumental learning — the ability to ...
Page 14
... infants . Perception , 11 , 173–186 . Leslie , A. M. ( 1984 ) . Infant perception of a manual pick - up event . British Journal of Developmental Psychology , 2 , 19–32 . architecture and domain specificity . In L. A. Hirschfeld & S. A. ...
... infants . Perception , 11 , 173–186 . Leslie , A. M. ( 1984 ) . Infant perception of a manual pick - up event . British Journal of Developmental Psychology , 2 , 19–32 . architecture and domain specificity . In L. A. Hirschfeld & S. A. ...
Page 15
... infant Science 208 , 1159–1161 . memory . motion : Continuity and inertia . Cognition , 51 , 131-176 . Spirtes , P ... Infants ' expectations about the motion of animate versus inanimate objects . Paper presented at the 15th annual ...
... infant Science 208 , 1159–1161 . memory . motion : Continuity and inertia . Cognition , 51 , 131-176 . Spirtes , P ... Infants ' expectations about the motion of animate versus inanimate objects . Paper presented at the 15th annual ...
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Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz Limited preview - 2007 |
Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz Limited preview - 2007 |
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actions adults algorithms Bayesian inference Bayesian networks behavior beliefs birth control pills blicket detector Cambridge causal Bayes nets causal inference causal knowledge causal learning causal Markov condition causal model causal networks causal power causal reasoning causal relations causal relationships causal strength causal structure causal system chapter Cognitive Science common cause computational condition conditional independence conditional probabilities correlation counterfactuals covariation cues deterministic Development Developmental Developmental Psychology domain effect evidence example experiments explanations Figure framework Fuel Intake Glymour Gopnik graph schema graphical models Griffiths Hagmayer human independent infants intervention interventionist intuitive theories Journal of Experimental Lagnado Laplace learners manipulated Markov Markov random field mechanism Meltzoff object observed outcome participants Piston predictions prior probabilistic probabilistic graphical models probability distribution psychological question Reichenbach represent representation Schulz Sloman Sobel specific statistical stickball Tenenbaum thrombosis tion trials underlying understanding unobserved cause variables Waldmann Wellman Woodward