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 ...
Page 11
That is, for learning to occur, cues have to be predictive: The probability of the effect given the cue must be greater than the probability of the effect in the absence of the cue. The Rescorla-Wagner theory (R-W theory; ...
That is, for learning to occur, cues have to be predictive: The probability of the effect given the cue must be greater than the probability of the effect in the absence of the cue. The Rescorla-Wagner theory (R-W theory; ...
Page 12
The account does not explain how, in the absence of prior knowledge or temporal cues, people could use data to distinguish causes and effects (i.e., to infer whether A causes B or B causes A). Put another way, both the R-W account ...
The account does not explain how, in the absence of prior knowledge or temporal cues, people could use data to distinguish causes and effects (i.e., to infer whether A causes B or B causes A). Put another way, both the R-W account ...
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Predictive and diagnostic learning within causal models: Asymmetries in cue competition. Journal of Experimental Psychology: General, 121, 222–236. Wasserman, E. A., & Berglan, L. R. (1998). Backward blocking and recovery from ...
Predictive and diagnostic learning within causal models: Asymmetries in cue competition. Journal of Experimental Psychology: General, 121, 222–236. Wasserman, E. A., & Berglan, L. R. (1998). Backward blocking and recovery from ...
Page 24
A cue stick strikes a cue ball, which in turn strikes the eight ball, causing it to drop into a pocket. The stick has been coated with blue chalk dust, some of which is transmitted to the cue ball and then to the eight ball as a result ...
A cue stick strikes a cue ball, which in turn strikes the eight ball, causing it to drop into a pocket. The stick has been coated with blue chalk dust, some of which is transmitted to the cue ball and then to the eight ball as a result ...
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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 |