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 5
In fact, the first applications of Bayes nets involved predicting conditional probabilities (Pearl, 1988). Many real-life inferences ... Predictions about probabilities may be quite different from predictions about interventions.
In fact, the first applications of Bayes nets involved predicting conditional probabilities (Pearl, 1988). Many real-life inferences ... Predictions about probabilities may be quite different from predictions about interventions.
Page 6
(We can also sometimes make accurate predictions about the effects of interventions that do not meet all these conditions). In causal Bayes nets, interventions systematically alter the nature of the graph they intervene on, ...
(We can also sometimes make accurate predictions about the effects of interventions that do not meet all these conditions). In causal Bayes nets, interventions systematically alter the nature of the graph they intervene on, ...
Page 8
Those representations allow children to make predictions, perform interventions, and even generate counterfactuals. As soon as they can talk, they even offer explanations of the world around them. And, they seem to learn those causal ...
Those representations allow children to make predictions, perform interventions, and even generate counterfactuals. As soon as they can talk, they even offer explanations of the world around them. And, they seem to learn those causal ...
Page 9
Finally, preschoolers' predictions, causal judgments, and counterfactual inferences are remarkably accurate across a wide range of tasks and content areas (e.g., Flavell, Green, & Flavell, 1995; Gelman & Wellman, 1991; Gopnik & Wellman, ...
Finally, preschoolers' predictions, causal judgments, and counterfactual inferences are remarkably accurate across a wide range of tasks and content areas (e.g., Flavell, Green, & Flavell, 1995; Gelman & Wellman, 1991; Gopnik & Wellman, ...
Page 11
The Rescorla-Wagner theory (R-W theory; 1972) specified that learning occurred on a trial-by-trial basis and predicted that early trials would be more important to learning than later trials. In its simplest form, the R-W equation for ...
The Rescorla-Wagner theory (R-W theory; 1972) specified that learning occurred on a trial-by-trial basis and predicted that early trials would be more important to learning than later trials. In its simplest form, the R-W equation for ...
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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 |
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 |