## 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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**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 independent in probability conditional on z. The ... Page 5

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**correlated**with partying, which leads to insomnia). But, intervening on their wine drinking, forbidding them from drinking, for example, will have no effect on their insomnia. Only intervening on partying will do that. The Bayes net ... Page 6

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**correlation**and draw a causal conclusion as a result. This type of learning, however, requires an additional assumption. The assumption is that the patterns of dependence and independence we see among the variables really are the result ... Page 15

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**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 Uncertainty in ... Page 20

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**correlated**with Y does not imply that manipulating X is a way of changing Y, while the claim that X causes Y does ...**correlated**, then X causes Y. (NC) If X causes Y, then (a) there are possible interventions that change the value of X ...### Other editions - View all

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 |

### Common terms and phrases

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