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 23
... mechanisms and to formulate a plausible relationship between causation and probabilities (for details, see Woodward, 2003, chapter 2). Of course, it is a separate question whether the notion corresponds to anything that is ...
... mechanisms and to formulate a plausible relationship between causation and probabilities (for details, see Woodward, 2003, chapter 2). Of course, it is a separate question whether the notion corresponds to anything that is ...
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... mechanism is present throughout this sequence. The problem is that there is nothing in all this information that ... mechanisms, properly understood, plays an important role 24 CAUSATION AND INTERVENTION.
... mechanism is present throughout this sequence. The problem is that there is nothing in all this information that ... mechanisms, properly understood, plays an important role 24 CAUSATION AND INTERVENTION.
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... mechanism information in causal attribution. This mechanism information can be readily reinterpreted as information about interventionist counterfactuals. For example, in Experiment 2, subjects must decide which of two different lamps ...
... mechanism information in causal attribution. This mechanism information can be readily reinterpreted as information about interventionist counterfactuals. For example, in Experiment 2, subjects must decide which of two different lamps ...
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... mechanism theories seem to imply. Causal Judgment and Interventionist Counterfactuals I noted that interventionist theories are just one species of the more general category of difference-making theories. The sensitivity of causal ...
... mechanism theories seem to imply. Causal Judgment and Interventionist Counterfactuals I noted that interventionist theories are just one species of the more general category of difference-making theories. The sensitivity of causal ...
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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