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Generalized Identity Matching in NARS
Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering. Stockholm Univ, Sweden.ORCID iD: 0000-0001-5547-3866
Stockholm Univ, Sweden.
Stockholm Univ, Sweden.
2023 (English)In: ARTIFICIAL GENERAL INTELLIGENCE, AGI 2022, SPRINGER INTERNATIONAL PUBLISHING AG , 2023, Vol. 13539, p. 243-249Conference paper, Published paper (Refereed)
Abstract [en]

Generalized identity matching is the ability to apply an identity concept in novel situations. This ability has been studied experimentally among humans and non-humans in a match-to-sample task. The aim of this study was to test if this ability was possible to demonstrate in the Non-Axiomatic Reasoning System (NARS). More specifically, we used a minimal configuration of OpenNARS for Applications that contained only sensorimotor reasoning. After training with only two identity matching-to-sample problems, NARS was able to derive an identity concept that it could generalize to novel situations.

Place, publisher, year, edition, pages
SPRINGER INTERNATIONAL PUBLISHING AG , 2023. Vol. 13539, p. 243-249
Series
Lecture Notes in Artificial Intelligence, ISSN 2945-9133
Keywords [en]
Identity matching; Animal intelligence; NARS
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:liu:diva-194207DOI: 10.1007/978-3-031-19907-3_23ISI: 000971476600023ISBN: 9783031199066 (print)ISBN: 9783031199073 (electronic)OAI: oai:DiVA.org:liu-194207DiVA, id: diva2:1761346
Conference
15th International Conference on Artificial General Intelligence (AGI), Seattle, WA, aug 19-22, 2022
Available from: 2023-06-01 Created: 2023-06-01 Last updated: 2025-02-07

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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