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Causal Status as a Determinant of Feature Centrality
- Cognitive Psychology
, 2000
"... this article. We also thank Denise Hatton, Tisha Baldwin, Joshua Nathan, Helen Sullivan, and Julia Wenzlaff for collecting data. Some of the stimulus materials used in Experiments 1 and 2 are adapted from the stimulus materials used in Rehder and Hastie (1997) and we thank them for inspiring many of ..."
Abstract
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Cited by 28 (2 self)
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this article. We also thank Denise Hatton, Tisha Baldwin, Joshua Nathan, Helen Sullivan, and Julia Wenzlaff for collecting data. Some of the stimulus materials used in Experiments 1 and 2 are adapted from the stimulus materials used in Rehder and Hastie (1997) and we thank them for inspiring many of the features and objects used in these studies. This project was supported by a National Science Foundation Grant (NSF-SBR 9515085) and a National Institute of Mental Health Grant (RO1 MH57737) given to Woo-kyoung Ahn, a National Science Foundation Graduate Fellowship to Nancy Kim, and a National Institute of Mental Health Postdoctoral Fellowship (MH10888-01A1) to Mary Lassaline
Why Are Different Features Central for Natural Kinds and Artifacts?: The Role of Causal Status in Determining Feature Centrality
, 1998
"... Ahn and Lassaline [Ahn, W., Lassaline, M.E., 1995. Causal structure in categorization. ..."
Abstract
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Cited by 21 (1 self)
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Ahn and Lassaline [Ahn, W., Lassaline, M.E., 1995. Causal structure in categorization.
A Bayesian Framework for Concept Learning
- DEPARTMENT OF ARTIFICIAL INTELLIGENCE, EDINBURGH UNIVERSITY
, 1999
"... Human concept learning presents a version of the classic problem of induction, which is made particularly difficult by the combination of two requirements: the need to learn from a rich (i.e. nested and overlapping) vocabulary of possible concepts and the need to be able to generalize concepts reaso ..."
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Cited by 15 (2 self)
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Human concept learning presents a version of the classic problem of induction, which is made particularly difficult by the combination of two requirements: the need to learn from a rich (i.e. nested and overlapping) vocabulary of possible concepts and the need to be able to generalize concepts reasonably from only a few positive examples. I begin this thesis by considering a simple number concept game as a concrete illustration of this ability. On this task, human learners can with reasonable confidence lock in on one out of a billion billion billion logically possible concepts, after seeing only four positive examples of the concept, and can generalize informatively after seeing just a single example. Neither of the two classic approaches to inductive inference -- hypothesis testing in a constrained space of possible rules and computing similarity to the observed examples -- can provide a complete picture of how people generalize concepts in even this simple setting. This thesis prop...
Causal Status Effect in Children's Categorization
, 2000
"... The current study examined the causal status effect (weighing cause features more than effect features in categorization) in children. Adults (Study 1) and 79-year-old children (Study 2) learned descriptions of novel animals, in which one feature caused two other features. When asked to determine wh ..."
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Cited by 7 (0 self)
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The current study examined the causal status effect (weighing cause features more than effect features in categorization) in children. Adults (Study 1) and 79-year-old children (Study 2) learned descriptions of novel animals, in which one feature caused two other features. When asked to determine which transfer item was more likely to be an example of the animal they had learned, both adults and children preferred an animal with a cause feature and an effect feature rather than an animal with two effect features. This study is the rst direct demonstration of the causal status effect in children. # 2000 Elsevier Science B.V. All rights reserved.

