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dc.contributor.authorSaariluoma, Pertti
dc.contributor.authorKarvonen, Antero
dc.contributor.authorSorsamäki, Lotta
dc.contributor.editorTropmann-Frick, Marina
dc.contributor.editorJaakkola, Hannu
dc.contributor.editorThalheim, Bernhard
dc.contributor.editorKiyoki, Yasushi
dc.contributor.editorYoshida, Naofumi
dc.date.accessioned2022-01-24T06:44:58Z
dc.date.available2022-01-24T06:44:58Z
dc.date.issued2021
dc.identifier.citationSaariluoma, P., Karvonen, A., & Sorsamäki, L. (2021). Human Digital Twins in Acquiring Information About Human Mental Processes for Cognitive Mimetics. In M. Tropmann-Frick, H. Jaakkola, B. Thalheim, Y. Kiyoki, & N. Yoshida (Eds.), <i>Information Modelling and Knowledge Bases XXXIII (EJC 2021)</i> (pp. 163-176). IOS Press. Frontiers in Artificial Intelligence and Applications, 343. <a href="https://doi.org/10.3233/faia210484" target="_blank">https://doi.org/10.3233/faia210484</a>
dc.identifier.otherCONVID_103920866
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/79485
dc.description.abstractModern information technology makes it possible to redesign the ways people work. In the future, machines can carry out intelligence-requiring tasks, which previously were done by people. It is thus good to develop methodologies for designing intelligent systems. An example of such methods is cognitive mimetics, i.e. imitating human information processing. Today, machines cannot by themselves navigate in archipelagos. However, the fact that people can take care of ship steering and navigation means that there is an information process, which makes it possible to navigate ships. This information process takes place inside the minds of navigating people. If we are able to explicate the information processing in the navigator’s mind, the knowledge of it can be used in designing intelligent machines. Replicating physical objects and industrial processes by means of digital computers is called digital twinning. Digital twins (DTs), which are digital replicas of physical systems and processes, have recently become tools for working with complex industrial processes. A crucial question for DTs is should human actions be added to them? As the answer is positive, such models of human information processing can be called human digital twins (HDTs). The knowledge of human tacit and explicit information processes can be represented by human digital twins. Models can be used in the search for a deeper understanding of human intelligent information processes. Human digital twins can thus be used as methodological tools in cognitive mimetics. In our present study, we modeled paper machine operators’ thinking. Specifically, we developed an ideal-exception-correction (IEC) model for paper operators’ control logic. The model illustrates how research and HDT-modeling can be used for explicating the subconscious or tacit information processing of people for the design of intelligent systems. In this article a model for design processes using cognitive modelling will be suggested. The concepts of cognitive mimetics and human digital twins enable us to outline a model for using the long tradition of simulating human thinking as a tool in designing intelligent systems.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherIOS Press
dc.relation.ispartofInformation Modelling and Knowledge Bases XXXIII (EJC 2021)
dc.relation.ispartofseriesFrontiers in Artificial Intelligence and Applications
dc.rightsCC BY-NC 4.0
dc.subject.otherdigital twins
dc.subject.otherhuman digital twins
dc.subject.othercognitive mimetics
dc.subject.othercognitive modelling
dc.titleHuman Digital Twins in Acquiring Information About Human Mental Processes for Cognitive Mimetics
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-202201241261
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineKoulutusteknologia ja kognitiotiedefi
dc.contributor.oppiaineKognitiotiedefi
dc.contributor.oppiaineLearning and Cognitive Sciencesen
dc.contributor.oppiaineCognitive Scienceen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.relation.isbn978-1-64368-242-6
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange163-176
dc.relation.issn0922-6389
dc.type.versionpublishedVersion
dc.rights.copyright© 2021 The authors and IOS Press.
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational conference on information modelling and knowledge bases
dc.subject.ysokognitiotiede
dc.subject.ysomallintaminen
dc.subject.ysokognitiiviset prosessit
dc.subject.ysotekoäly
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p16969
jyx.subject.urihttp://www.yso.fi/onto/yso/p3533
jyx.subject.urihttp://www.yso.fi/onto/yso/p5283
jyx.subject.urihttp://www.yso.fi/onto/yso/p2616
dc.rights.urlhttps://creativecommons.org/licenses/by-nc/4.0/
dc.relation.doi10.3233/faia210484
dc.type.okmA4


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