1. osnaDocs
  2. Fachbereich 08 - Humanwissenschaften
  3. FB08 - E-Dissertationen

Using Conceptual Spaces for Artificial Intelligence

Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://doi.org/10.48693/435
Open Access logo originally created by the Public Library of Science (PLoS)
Langanzeige der Metadaten
DC ElementWertSprache
dc.contributor.advisorProf. Dr. Kai-Uwe Kühnbergerger
dc.creatorBechberger, Lucas-
dc.date.accessioned2023-12-01T17:21:19Z-
dc.date.available2023-12-01T17:21:19Z-
dc.date.issued2023-12-01T17:21:19Z-
dc.identifier.urihttps://doi.org/10.48693/435-
dc.identifier.urihttps://osnadocs.ub.uni-osnabrueck.de/handle/ds-2023120110100-
dc.description.abstractThis dissertation makes the cognitive framework of conceptual spaces (mainly developed by Peter Gärdenfors) usable for practical applications in cognitive AI by providing a thorough mathematical formalization of the framework along with an open source implementation, by proposing and evaluating a novel hybrid approach for connecting raw sensory information to the conceptual layer of representation, and by discussing various learning mechanisms for identifying conceptual regions. It provides a tight integration of various topics such as cognitive AI, neural-symbolic integration, deep representation learning, multidimensional scaling on psychological dissimilarity ratings, and commonsense reasoning.eng
dc.rightsAttribution 3.0 Germany*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/de/*
dc.subjectConceptual Spaceseng
dc.subjectMachine Learningeng
dc.subjectMultidimensional Scalingeng
dc.subjectCognitive AIeng
dc.subjectSymbol Groundingeng
dc.subject.ddc004 - Informatikger
dc.titleUsing Conceptual Spaces for Artificial Intelligenceeng
dc.typeDissertation oder Habilitation [doctoralThesis]-
thesis.locationOsnabrück-
thesis.institutionUniversität-
thesis.typeDissertation [thesis.doctoral]-
thesis.date2023-03-14-
dc.contributor.refereeProf. Dr. Antonio Lietoger
dc.contributor.refereeProf. Dr. Rob Goldstoneger
dc.subject.bk54.72 - Künstliche Intelligenzger
dc.subject.bk54.74 - Maschinelles Sehenger
dc.subject.ccsI.2.4 - Knowledge Representation Formalisms and Methodsger
dc.subject.ccsI.2.10 - Vision and Scene Understandingger
dc.subject.ccsI.2.4 - Knowledge Representation Formalisms and Methodsger
dc.subject.ccsI.2.6 - Learningger
Enthalten in den Sammlungen:FB08 - E-Dissertationen

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
thesis_bechberger.pdfPräsentationsformat44,53 MBAdobe PDF
thesis_bechberger.pdf
Miniaturbild
Öffnen/Anzeigen
Zur Kurzanzeige


Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons Creative Commons