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 vii
Contents PART I: Contributors ix Introduction 1 Alison Gopnik and Laura Schulz CAUSATION AND INTERVENTION 1 Interventionist Theories of Causation in Psychological Perspective 19 Jim Woodward 2 Infants' Causal Learning: Intervention, ...
Contents PART I: Contributors ix Introduction 1 Alison Gopnik and Laura Schulz CAUSATION AND INTERVENTION 1 Interventionist Theories of Causation in Psychological Perspective 19 Jim Woodward 2 Infants' Causal Learning: Intervention, ...
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And, there is no real learning involved in development but only triggering or enrichment. ... I mean, I'll tell you all about causal learning in psychology if you'll explain those directed acyclic graphs in plain English words?
And, there is no real learning involved in development but only triggering or enrichment. ... I mean, I'll tell you all about causal learning in psychology if you'll explain those directed acyclic graphs in plain English words?
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Given the faithfulness assumption, it is possible to infer complex causal structure from patterns of conditional probability and intervention (Glymour & Cooper, 1999; Spirtes et al., 1993). Computationally tractable learning algorithms ...
Given the faithfulness assumption, it is possible to infer complex causal structure from patterns of conditional probability and intervention (Glymour & Cooper, 1999; Spirtes et al., 1993). Computationally tractable learning algorithms ...
Page 8
Your computers may or may not be able to solve this causal learning problem, but it's certain that my sprogs can do it. In fact, they might be the most powerful causal learning devices in the universe. Thirty years of work on the ...
Your computers may or may not be able to solve this causal learning problem, but it's certain that my sprogs can do it. In fact, they might be the most powerful causal learning devices in the universe. Thirty years of work on the ...
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Nativist and Modular Views of Causal Reasoning Over the past several decades, however—and with the development of new methods for assessing the cognitive abilities of infants and young children— considerable research has suggested that ...
Nativist and Modular Views of Causal Reasoning Over the past several decades, however—and with the development of new methods for assessing the cognitive abilities of infants and young children— considerable research has suggested that ...
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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 |