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dc.contributor.authorKuwertz, Achim Christian
dc.date.accessioned2025-03-07T20:37:57Z
dc.date.available2025-03-07T20:37:57Z
dc.date.issued2022
dc.date.submitted2022-12-05T15:40:40Z
dc.identifierONIX_20221205_9783731512196_10
dc.identifier1863-6489
dc.identifierhttps://library.oapen.org/handle/20.500.12657/59837
dc.identifier.urihttps://doab-dev.siscern.org/handle/20.500.12854/165999
dc.description.abstractIn this work, an approach for adaptive world modeling is proposed. World models for cognitive systems often employ predefined domain models, which may become insufficient when encountering unforeseen entities. The presented approach addresses an adaptive extension of such domain models, considering the relevance of proposed model adaptations. As a basis, a quantitative model evaluation is devised, rating the ability of a domain model to represent the currently observed environment state.
dc.languageGerman
dc.relation.ispartofseriesKarlsruher Schriften zur Anthropomatik
dc.rightsopen access
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
dc.subject.otherUmweltmodellierung
dc.subject.otherquantitative Modellbewertung
dc.subject.otherprobabilistische Informationsverarbeitung
dc.subject.otherKonzeptlernen
dc.subject.otherkognitive Systeme
dc.subject.otherworld modeling
dc.subject.otherquantitative model evaluation
dc.subject.otherconcept learning
dc.subject.otherprobabilistic information processing
dc.subject.othercognitive systems
dc.titleAdaptive Umweltmodellierung für kognitive Systeme in offener Welt durch dynamische Konzepte und quantitative Modellbewertung
dc.typebook
oapen.identifier.doi10.5445/KSP/1000148667
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2
oapen.relation.isbn9783731512196
oapen.collectionAG Universitätsverlage
oapen.imprintKIT Scientific Publishing
oapen.pages440
oapen.place.publicationKarlsruhe
peerreview.review.typeFull text
peerreview.anonymityAll identities known
peerreview.reviewer.typeEditorial board member
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityBooks or series editor
peerreview.id51a542ec-eaeb-47c2-861d-6022e981a97a
dc.seriesnumber57
dc.abstractotherlanguageIn this work, an approach for adaptive world modeling is proposed. World models for cognitive systems often employ predefined domain models, which may become insufficient when encountering unforeseen entities. The presented approach addresses an adaptive extension of such domain models, considering the relevance of proposed model adaptations. As a basis, a quantitative model evaluation is devised, rating the ability of a domain model to represent the currently observed environment state.
peerreview.titleDissertations in Series (Dissertationen in Schriftenreihe)


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