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Causal Learning: Psychology, Philosophy, and Computation PDF

371 Pages·2007·2.493 MB·English
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by Alison Gopnik, Laura Schulz| 2007| 371 pages| 2.493| English

About Causal Learning: Psychology, Philosophy, and Computation

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.

Detailed Information

Author:Alison Gopnik, Laura Schulz
Publication Year:2007
ISBN:9781435600508
Pages:371
Language:English
File Size:2.493
Format:PDF
Price:FREE
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