Title

Category and feature identification.

Date of Original Version

3-1-2010

Type

Article

PubMed ID

20080224

Abstract or Description

This paper considers a family of inductive problems where reasoners must identify familiar categories or features on the basis of limited information. Problems of this kind are encountered, for example, when word learners acquire novel labels for pre-existing concepts. We develop a probabilistic model of identification and evaluate it in three experiments. Our first two experiments explore problems where a single category or feature must be identified, and our third experiment explores cases where participants must combine several pieces of information in order to simultaneously identify a category and a feature. Humans readily solve all of these problems, and we show that our model accounts for human inferences better than several alternative approaches.

DOI

10.1016/j.actpsy.2009.11.012

 

Published In

Acta Psychologica, 133, 3, 216-233.