Causal Learning: Psychology, Philosophy, and ComputationUnderstanding 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. |
From inside the book
Results 1-5 of 40
Page vii
Contents PART I: Contributors ix Introduction 1 Alison Gopnik and Laura Schulz CAUSATION AND INTERVENTION 1 Interventionist Theories of Causation in Psychological Perspective 19 Jim Woodward 2 Infants' Causal Learning: Intervention, ...
Contents PART I: Contributors ix Introduction 1 Alison Gopnik and Laura Schulz CAUSATION AND INTERVENTION 1 Interventionist Theories of Causation in Psychological Perspective 19 Jim Woodward 2 Infants' Causal Learning: Intervention, ...
Page 13
The unsolved problems you describe in the psychology of causal learning—the things you say your sprogs are so good at doing and the theories are so bad at explaining—well, they're just the sort of things that the interventionist/causal ...
The unsolved problems you describe in the psychology of causal learning—the things you say your sprogs are so good at doing and the theories are so bad at explaining—well, they're just the sort of things that the interventionist/causal ...
Page 17
Psychology, Philosophy, and Computation Alison Gopnik, Laura Schulz. Part I CAUSATION AND INTERVENTION This page intentionally left blank Interventionist Theories of Causation in PART I: CAUSATION AND INTERVENTION.
Psychology, Philosophy, and Computation Alison Gopnik, Laura Schulz. Part I CAUSATION AND INTERVENTION This page intentionally left blank Interventionist Theories of Causation in PART I: CAUSATION AND INTERVENTION.
Page 18
Psychology, Philosophy, and Computation Alison Gopnik, Laura Schulz. This page intentionally left blank Interventionist Theories of Causation in.
Psychology, Philosophy, and Computation Alison Gopnik, Laura Schulz. This page intentionally left blank Interventionist Theories of Causation in.
Page 19
The interventionist theory described in the next section is a version of a counterfactual theory; the counterfactuals in question describe what would happen to E under interventions (idealized manipulations of) on C. The interventionist ...
The interventionist theory described in the next section is a version of a counterfactual theory; the counterfactuals in question describe what would happen to E under interventions (idealized manipulations of) on C. The interventionist ...
What people are saying - Write a review
We haven't found any reviews in the usual places.
Other editions - View all
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 |
Common terms and phrases
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
Bibliographic information
| Title | Causal Learning: Psychology, Philosophy, and Computation Oxford Series in Cognitive Development |
| Editors | Alison Gopnik, Laura Schulz |
| Publisher | Oxford University Press, 2007 |
| ISBN | 019803928X, 9780198039280 |
| Length | 384 pages |
| Subjects | › Psychology / Cognitive Psychology & Cognition |
| Export Citation | BiBTeX EndNote RefMan |