Syntactic principles of heuristic-driven theory projection

Autor(en): Schwering, Angela
Krumnack, Ulf 
Kuehnberger, Kai-Uwe 
Gust, Helmar
Stichwörter: Analogical learning; Analogy; Anti-unification; Computer Science; Computer Science, Artificial Intelligence; Logic based analogical reasoning; Neurosciences; Neurosciences & Neurology; Psychology; Psychology, Experimental
Erscheinungsdatum: 2009
Herausgeber: ELSEVIER
Journal: COGNITIVE SYSTEMS RESEARCH
Volumen: 10
Ausgabe: 3
Startseite: 251
Seitenende: 269
Zusammenfassung: 
Analogy making is a central construct in human cognition and plays an important role to explain cognitive abilities. While various psychologically or neurally inspired theories for analogical reasoning have been proposed, there is a lack of a logical foundation for analogical reasoning in artificial intelligence and cognitive science. We aim to close this gap and propose heuristic-driven theory projection (HDTP), a mathematically sound framework for analogy making. HDTP represents knowledge about the source and the target domain as first-order logic theories and compares them for structural commonalities using anti-unification. The paper provides an overview of the syntactic principles of HDTP, explains all phases of analogy making at a formal level, and illustrates these phases with examples. (C) 2009 Elsevier B.V. All rights reserved.
Beschreibung: 
Conference on Nature, Science, and Social Movements, Univ Aegean, Mytilene, GREECE, JUN 25-28, 2004
ISSN: 13890417
DOI: 10.1016/j.cogsys.2008.09.002

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