Domain transfer via cross-domain analogy

Matthew Klenk*, Kenneth D Forbus

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Analogical learning has long been seen as a powerful way of extending the reach of one's knowledge. We present the domain transfer via analogy (DTA) method for learning new domain theories via cross-domain analogy. Our model uses analogies between pairs of textbook example problems, or worked solutions, to create a domain mapping between a familiar and a new domain. This mapping allows us to initialize a new domain theory. After this initialization, another analogy is made between the domain theories themselves, providing additional conjectures about the new domain. We present two experiments in which our model learns rotational kinematics by an analogy with translational kinematics, and vice versa. These learning rates outperform those from a version of the system that is incrementally given the correct domain theory.

Original languageEnglish (US)
Pages (from-to)240-250
Number of pages11
JournalCognitive Systems Research
Volume10
Issue number3
DOIs
StatePublished - Sep 2009

Keywords

  • Cross-domain analogy
  • Learning

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

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