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 1
... independent of the variables in S conditional on any set of values of the variables that are parents of R! Let me give you a brief sense of where I'm coming from, as we say in mellow Arcadia (though I'm a New Yorker myself). I went to ...
... independent of the variables in S conditional on any set of values of the variables that are parents of R! Let me give you a brief sense of where I'm coming from, as we say in mellow Arcadia (though I'm a New Yorker myself). I went to ...
Page 4
... independent in probability if and only if for every value x of X and y of Y the probability of x and y occurring together equals the unconditional probability of x multiplied by the unconditional probability of y. That is p(x & y)p(x) ...
... independent in probability if and only if for every value x of X and y of Y the probability of x and y occurring together equals the unconditional probability of x multiplied by the unconditional probability of y. That is p(x & y)p(x) ...
Page 5
... independent (in probability) of the probability of party going occurring conditional on the occurrence of wine drinking. If Graph 2 is right and parties are a common cause of wine and insomnia, then I ⊥W | P; the probability of wine ...
... independent (in probability) of the probability of party going occurring conditional on the occurrence of wine drinking. If Graph 2 is right and parties are a common cause of wine and insomnia, then I ⊥W | P; the probability of wine ...
Page 12
... independently; (b) that there are no unobserved common causes of the candidate cause and the effect (although the account can be generalized to relax this assumption; Glymour, 2001); and (c) that candidate causes are noninteractive ...
... independently; (b) that there are no unobserved common causes of the candidate cause and the effect (although the account can be generalized to relax this assumption; Glymour, 2001); and (c) that candidate causes are noninteractive ...
Page 21
... independent of A and B and then, depending on the output of this device, experimentally imposing (or “setting”) B to some particular value. Under any such intervention, the value of S will no longer be correlated with the value of B ...
... independent of A and B and then, depending on the output of this device, experimentally imposing (or “setting”) B to some particular value. Under any such intervention, the value of S will no longer be correlated with the value of B ...
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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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