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 4
When we say three variables x, y, and z are correlated, we mean that they are dependent in probability. When we say that x and y are correlated but that that correlation disappears when z is partialed out, we mean that x and y are ...
When we say three variables x, y, and z are correlated, we mean that they are dependent in probability. When we say that x and y are correlated but that that correlation disappears when z is partialed out, we mean that x and y are ...
Page 5
If that structure is the correct one, then knowing that someone drank wine will indeed make you more likely to predict that they will have insomnia (because drinking wine is correlated with partying, which leads to insomnia).
If that structure is the correct one, then knowing that someone drank wine will indeed make you more likely to predict that they will have insomnia (because drinking wine is correlated with partying, which leads to insomnia).
Page 6
In effect, what you did was to “partial out” the effects of partying on the wine-insomnia correlation and draw a causal conclusion as a result. This type of learning, however, requires an additional assumption.
In effect, what you did was to “partial out” the effects of partying on the wine-insomnia correlation and draw a causal conclusion as a result. This type of learning, however, requires an additional assumption.
Page 15
Cause and correlation in biology. Oxford, England: Oxford University Press. Silva, R., Scheines, R., Glymour, C., & Spirtes, P. (2003). Learning measurement models for unobserved variables. Proceedings of the 18th Conference on ...
Cause and correlation in biology. Oxford, England: Oxford University Press. Silva, R., Scheines, R., Glymour, C., & Spirtes, P. (2003). Learning measurement models for unobserved variables. Proceedings of the 18th Conference on ...
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The claim that X is correlated with Y does not imply that manipulating X is a way of changing Y, while the claim that X causes Y does have this implication. And, given the strong interest that humans and other animals have in finding ...
The claim that X is correlated with Y does not imply that manipulating X is a way of changing Y, while the claim that X causes Y does have this implication. And, given the strong interest that humans and other animals have in finding ...
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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 |