Modeling Learning via Progressive Alignment using Interim Generalizations

Subu Kandaswamy, Ken Forbus, Dedre Gentner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

There is ample empirical evidence that children can sometimes learn during the course of even a few experimental trials. We propose that one mechanism for this is the use of analogical generalizations constructed in working memory, producing what we call interim generalizations. Prior research suggests that such generalizations can be constructed when there is high similarity between closely spaced items. This paper describes how structure-mapping simulations can be adapted to capture this phenomenon, using automatically encoded stimuli. It is an advance over prior models in that it automatically detects when rerepresentation should be tried and carries it out to improve its performance.
Original languageEnglish (US)
Title of host publicationProceedings of the 36th Annual Conference of the Cognitive Science Society
EditorsPaul Bello, Marcello Guarini, Marjorie McShane, Brian Scassellati
PublisherCognitive Science Society
Pages2471-2476
Number of pages6
ISBN (Print)978-0991196708
StatePublished - 2014
EventCogSci 2014 - Quebec City, Canada
Duration: Jul 1 2014 → …

Conference

ConferenceCogSci 2014
Period7/1/14 → …

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