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dc.contributor.authorTerziyan, Vagan
dc.contributor.authorTiihonen, Timo
dc.date.accessioned2024-03-27T12:38:50Z
dc.date.available2024-03-27T12:38:50Z
dc.date.issued2024
dc.identifier.citationTerziyan, V., & Tiihonen, T. (2024). Using Cloning-GAN Architecture to Unlock the Secrets of Smart Manufacturing : Replication of Cognitive Models. <i>Procedia Computer Science</i>, <i>232</i>, 890-902. <a href="https://doi.org/10.1016/j.procs.2024.01.089" target="_blank">https://doi.org/10.1016/j.procs.2024.01.089</a>
dc.identifier.otherCONVID_207724540
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/94096
dc.description.abstractAs Industry 4.0 and 5.0 evolve to be highly automated but human-centric, there is a need for process modeling based on digital replicas of physical objects including humans. Knowledge distillation and cognitive cloning offer a way to train operational copies of decision-making black boxes, or donors, without requiring additional data. In this paper, we propose an architecture and analytics for a generative adversarial network, called Cloning-GAN, which enables donor-clone knowledge transfer, including the donor's individual biases. The architecture involves generating challenging samples to be labeled by the donor and used as training data for the clone. We consider several multicriteria requirements for the generated data, including closeness to the decision boundary, uniform distribution in the decision space, maximal confusion for the donor, and challenge for the clone. We present various strategies to balance these conflicting criteria forcing the clone learning quickly the hidden cognitive skills and biases of the donor. See presentation slides: https://ai.it.jyu.fi/ISM-2023-Cloning_GAN.pptxen
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofseriesProcedia Computer Science
dc.rightsCC BY-NC-ND 4.0
dc.subject.othersmart manufacturing
dc.subject.otherdigital twins
dc.subject.othercognitive clones
dc.subject.otherknowledge transfer
dc.subject.otherknowledge distillation
dc.subject.othergenerative adversarial network
dc.subject.otheradversarial distillation
dc.titleUsing Cloning-GAN Architecture to Unlock the Secrets of Smart Manufacturing : Replication of Cognitive Models
dc.typeresearch article
dc.identifier.urnURN:NBN:fi:jyu-202403272640
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange890-902
dc.relation.issn1877-0509
dc.relation.volume232
dc.type.versionpublishedVersion
dc.rights.copyright© 2024 the Authors
dc.rights.accesslevelopenAccessfi
dc.type.publicationarticle
dc.subject.ysotiedonsiirto
dc.subject.ysokopiot
dc.subject.ysokloonaus
dc.subject.ysoosaamisen siirto
dc.subject.ysokloonit
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p5429
jyx.subject.urihttp://www.yso.fi/onto/yso/p14833
jyx.subject.urihttp://www.yso.fi/onto/yso/p17448
jyx.subject.urihttp://www.yso.fi/onto/yso/p10345
jyx.subject.urihttp://www.yso.fi/onto/yso/p20737
dc.rights.urlhttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.relation.doi10.1016/j.procs.2024.01.089
dc.type.okmA1


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