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 v
... human experiences, even better than you think it is going to be, and we are extremely grateful to everyone at that magnificent institution, particularly Douglas Adams and Mark Turner, the then-directors, and the staff who made ...
... human experiences, even better than you think it is going to be, and we are extremely grateful to everyone at that magnificent institution, particularly Douglas Adams and Mark Turner, the then-directors, and the staff who made ...
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... Human Categorization 173 David Danks 12 Essentialism as a Generative Theory of Classification 190 Bob Rehder Data-Mining Probabilists or Experimental Determinists? A Dialogue on the Principles Underlying Causal Learning in Children 208 ...
... Human Categorization 173 David Danks 12 Essentialism as a Generative Theory of Classification 190 Bob Rehder Data-Mining Probabilists or Experimental Determinists? A Dialogue on the Principles Underlying Causal Learning in Children 208 ...
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... Human Growth and Development University of Michigan Ann Arbor, MI 48103 Jim Woodward Division of the Humanities and Social Sciences California Institute of Technology Pasadena, CA 91125 Introduction Alison Gopnik & Laura Schulz From ...
... Human Growth and Development University of Michigan Ann Arbor, MI 48103 Jim Woodward Division of the Humanities and Social Sciences California Institute of Technology Pasadena, CA 91125 Introduction Alison Gopnik & Laura Schulz From ...
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... human causal learning. The causal Markov assumption, however, applies to all parameterizations. To illustrate, consider a simple causal problem that is far too common for academics who attend many learned conferences. Suppose that I ...
... human causal learning. The causal Markov assumption, however, applies to all parameterizations. To illustrate, consider a simple causal problem that is far too common for academics who attend many learned conferences. Suppose that I ...
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... human or robotic, sprog, or Ph.D. could infer the structure of a threedimensional world from two-dimensional data. Vision science tells us that the visual system implicitly assumes that there is a world of threedimensional moving ...
... human or robotic, sprog, or Ph.D. could infer the structure of a threedimensional world from two-dimensional data. Vision science tells us that the visual system implicitly assumes that there is a world of threedimensional moving ...
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Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz Limited preview - 2007 |
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