A Probabilistic Model of Theory Formation

Autor/inn/en	Kemp, Charles; Tenenbaum, Joshua B.; Niyogi, Sourabh; Griffiths, Thomas L.
Titel	A Probabilistic Model of Theory Formation
Quelle	In: Cognition, 114 (2010) 2, S.165-196 (32 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0010-0277
DOI	10.1016/j.cognition.2009.09.003
Schlagwörter	Family Relationship; Logical Thinking; Models; Concept Formation; Comparative Analysis; Prediction; Learning Processes; Learning Theories; Behavioral Science Research + Suchen Sie Ihr Suchwort? Analogiemodell; Concept learning; Begriffsbildung; Vorhersage; Learning process; Lernprozess; Learning theory; Lerntheorie
Abstract	Concept learning is challenging in part because the meanings of many concepts depend on their relationships to other concepts. Learning these concepts in isolation can be difficult, but we present a model that discovers entire systems of related concepts. These systems can be viewed as simple theories that specify the concepts that exist in a domain, and the laws or principles that relate these concepts. We apply our model to several real-world problems, including learning the structure of kinship systems and learning ontologies. We also compare its predictions to data collected in two behavioral experiments. Experiment 1 shows that our model helps to explain how simple theories are acquired and used for inductive inference. Experiment 2 suggests that our model provides a better account of theory discovery than a more traditional alternative that focuses on features rather than relations. (Contains 4 tables and 18 figures.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10