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 | Enthalten in: | COGNITIVE SYSTEMS RESEARCH | Band: | 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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