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 24
... example, the presence A of lactose in the environment of Escherichia coli results in the production C of a protein that initiates transcription of the enzyme that digests lactose by interfering with the operation B of an agent that (in ...
... example, the presence A of lactose in the environment of Escherichia coli results in the production C of a protein that initiates transcription of the enzyme that digests lactose by interfering with the operation B of an agent that (in ...
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... example, in Experiment 2, subjects must decide which of two different lamps is responsible for the light projected on a wall. Here, the relevant interventionist counterfactuals will describe the relationship between turning on the lamp ...
... example, in Experiment 2, subjects must decide which of two different lamps is responsible for the light projected on a wall. Here, the relevant interventionist counterfactuals will describe the relationship between turning on the lamp ...
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... example, both exhibit backward blocking, and both rat behavior and human causal judgment are subject to a discounting or signaling effect in which the usual reaction of nonresponse to a noncontingent reward schedule does not occur when ...
... example, both exhibit backward blocking, and both rat behavior and human causal judgment are subject to a discounting or signaling effect in which the usual reaction of nonresponse to a noncontingent reward schedule does not occur when ...
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... example, that if they want to avoid getting their fingers inky they should use a pencil rather than a pen, that using a pen with blue ink rather than black ink will not avoid the outcome, and so on. If we think of counterfactuals of ...
... example, that if they want to avoid getting their fingers inky they should use a pencil rather than a pen, that using a pen with blue ink rather than black ink will not avoid the outcome, and so on. If we think of counterfactuals of ...
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Causal Learning: Psychology, Philosophy, and Computation Alison Gopnik,Laura Schulz Limited preview - 2007 |
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actions adults algorithms Bayesian inference Bayesian networks behavior beliefs birth control pills blicket detector Cambridge causal Bayes nets causal chain causal inference causal knowledge causal learning causal Markov condition causal model causal networks causal power causal reasoning causal relations causal relationships causal strength causal structure causal system chapter Cognitive Science common cause computational condition conditional independence conditional probabilities correlation counterfactuals covariation cues deterministic Development Developmental Psychology domain effect evidence example experiments explanations Figure framework Fuel Intake Glymour Gopnik graph schema graphical models Hagmayer human independent infants intervention interventionist intuitive theories Lagnado Laplace learners manipulated Markov Markov random field mechanism Meltzoff object observed outcome participants people’s Piston predictions prior probabilistic probabilistic graphical models probability distribution psychological question Reichenbach represent representation Schulz Sloman Sobel specific statistical stickball Tenenbaum thrombosis tion trials underlying understanding unobserved cause variables Waldmann Wellman Woodward