Computational models of analogy

Dedre Gentner*, Kenneth D. Forbus

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

87 Scopus citations

Abstract

Analogical mapping is a core process in human cognition. A number of valuable computational models of analogy have been created, capturing aspects of how people compare representations, retrieve potential analogs from memory, and learn from the results. In the past 25 years, this area has progressed rapidly, fueled by strong collaboration between psychologists and Artificial Intelligence (AI) scientists, with contributions from linguists and philosophers as well. There is now considerable consensus regarding the constraints governing the mapping process. However, computational models still differ in their focus, with some aimed at capturing the range of analogical phenomena at the cognitive level and others aimed at modeling how analogical processes might be implemented in neural systems. Some recent work has focused on modeling interactions between analogy and other processes, and on modeling analogy as a part of larger cognitive systems.

Original languageEnglish (US)
Pages (from-to)266-276
Number of pages11
JournalWiley Interdisciplinary Reviews: Cognitive Science
Volume2
Issue number3
DOIs
StatePublished - May 1 2011

ASJC Scopus subject areas

  • Neuroscience(all)
  • Psychology(all)

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