Causal learning: psychology, philosophy, and computation

New York: Oxford University Press (2007)
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Abstract

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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Alison Gopnik
University of California, Berkeley

Citations of this work

Mechanistic Evidence: Disambiguating the Russo–Williamson Thesis.Phyllis McKay Illari - 2011 - International Studies in the Philosophy of Science 25 (2):139-157.
The Causal Autonomy of the Special Sciences.Peter Menzies & Christian List - 2010 - In Cynthia McDonald & Graham McDonald (eds.), Emergence in Mind. Oxford, U.K.: Oxford University Press. pp. 108-129.
Must, knowledge, and (in)directness.Daniel Lassiter - 2016 - Natural Language Semantics 24 (2):117-163.

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