Causal Learning: Psychology, Philosophy, and ComputationUnderstanding 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 viii
10 11 13 8 Teaching the Normative Theory of Causal Reasoning 119 Richard Scheines, Matt Easterday, and David Danks 9 Interactions Between Causal and Statistical Learning 139 David M. Sobel and Natasha Z. Kirkham Beyond Covariation: Cues ...
10 11 13 8 Teaching the Normative Theory of Causal Reasoning 119 Richard Scheines, Matt Easterday, and David Danks 9 Interactions Between Causal and Statistical Learning 139 David M. Sobel and Natasha Z. Kirkham Beyond Covariation: Cues ...
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The covariation among the variables by itself is consistent with both these structures. You can discriminate between these two graphs by looking at the patterns of conditional probability among the three variables.
The covariation among the variables by itself is consistent with both these structures. You can discriminate between these two graphs by looking at the patterns of conditional probability among the three variables.
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In an influential monograph on children's causal reasoning, the psychologist Thomas Shultz distinguished between a statistical view of causal relations, in which the causal connection between events is determined by the covariation of ...
In an influential monograph on children's causal reasoning, the psychologist Thomas Shultz distinguished between a statistical view of causal relations, in which the causal connection between events is determined by the covariation of ...
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Covariation Accounts However, the generative transmission view of causation in particular and domain-specific ... largely focused on the role of contingency and covariation in causal learning, as opposed to principles about mechanisms.
Covariation Accounts However, the generative transmission view of causation in particular and domain-specific ... largely focused on the role of contingency and covariation in causal learning, as opposed to principles about mechanisms.
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Cheng proposes that people innately treat covariation as an index of causal power (an unobservable entity) and suggests that people reason about causes with respect to particular focal sets, a contextually determined set of events over ...
Cheng proposes that people innately treat covariation as an index of causal power (an unobservable entity) and suggests that people reason about causes with respect to particular focal sets, a contextually determined set of events over ...
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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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Bibliographic information
| Title | Causal Learning: Psychology, Philosophy, and Computation Oxford Series in Cognitive Development |
| Editors | Alison Gopnik, Laura Schulz |
| Publisher | Oxford University Press, 2007 |
| ISBN | 019803928X, 9780198039280 |
| Length | 384 pages |
| Subjects | › Psychology / Cognitive Psychology & Cognition |
| Export Citation | BiBTeX EndNote RefMan |