An Integrated Account of Generalization across Objects and Features

Autor/inn/en	Kemp, Charles; Shafto, Patrick; Tenenbaum, Joshua B.
Titel	An Integrated Account of Generalization across Objects and Features
Quelle	In: Cognitive Psychology, 64 (2012) 1-2, S.35-73 (39 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0010-0285
DOI	10.1016/j.cogpsych.2011.10.001
Schlagwörter	Generalization; Logical Thinking; Inferences; Probability; Problem Solving; Animals; Visual Perception; Classification; Causal Models + Suchen Sie Ihr Suchwort? Inference; Inferenz; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Problemlösen; Animal; Tier; Tiere; Visuelle Wahrnehmung; Classification system; Klassifikation; Klassifikationssystem; Kausalanalyse
Abstract	Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single feature that is unobserved for one or more objects. We explore problems where people must make inferences about multiple objects and features, and propose that people solve these problems by integrating knowledge about features with knowledge about objects. We evaluate three computational methods for integrating multiple systems of knowledge: the output combination approach combines the outputs produced by these systems, the distribution combination approach combines the probability distributions captured by these systems, and the structure combination approach combines a graph structure over features with a graph structure over objects. Three experiments explore problems where participants make inferences that draw on causal relationships between features and taxonomic relationships between animals, and we find that the structure combination approach provides the best account of our data. (Contains 20 figures and 3 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10