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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Page 4
... can be discrete (like school grade) or continuous (like weight); they can be binary (like “having eyes” or “not having eyes”) or take a range of values (like color). Similarly, the direct causal relations can have many forms; they can ...
... can be discrete (like school grade) or continuous (like weight); they can be binary (like “having eyes” or “not having eyes”) or take a range of values (like color). Similarly, the direct causal relations can have many forms; they can ...
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... can be represented by replacing the original graph with an altered graph in which arrows directed into the intervened on variable are eliminated (Judea Pearl in 2000 vividly referred to this process as graph surgery). The conditional ...
... can be represented by replacing the original graph with an altered graph in which arrows directed into the intervened on variable are eliminated (Judea Pearl in 2000 vividly referred to this process as graph surgery). The conditional ...
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... can be responsible for psychological effects and vice versa), and why causal reasoning is sensitive to patterns of evidence. Nonetheless, the majority of post-Piagetian research on preschool children's causal reasoning has emphasized ...
... can be responsible for psychological effects and vice versa), and why causal reasoning is sensitive to patterns of evidence. Nonetheless, the majority of post-Piagetian research on preschool children's causal reasoning has emphasized ...
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... can be applied to human causal learning by substituting causes for the conditioned stimulus and effects for the unconditioned stimulus. The associative strength between the two variables is then taken as indicating the causal connection ...
... can be applied to human causal learning by substituting causes for the conditioned stimulus and effects for the unconditioned stimulus. The associative strength between the two variables is then taken as indicating the causal connection ...
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... can be estimated as 1P(e |~c). Thus, generative causal power pc can be estimated as pc P/(1 P(e |~c)). As this equation illustrates, when alternative causes are absent, P will reflect the causal power of c. However, as P(e |~c) ...
... can be estimated as 1P(e |~c). Thus, generative causal power pc can be estimated as pc P/(1 P(e |~c)). As this equation illustrates, when alternative causes are absent, P will reflect the causal power of c. However, as P(e |~c) ...
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Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz Limited preview - 2007 |
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