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dc.contributor.authorFlores Solorio, Victor
dc.contributor.authorGarcia, Juan Pablo
dc.contributor.authorCeballos Cansino, Héctor Gibrán
dc.date.accessioned2019-11-07T20:27:12Z
dc.date.available2019-11-07T20:27:12Z
dc.date.issued2015-05-05
dc.identifier.isbn978-3-319-26184-3
dc.identifier.isbn978-3-319-26183-6
dc.identifier.issn03029743
dc.identifier.doihttps://doi.org/10.1007/978-3-319-26184-3_4
dc.identifier.urihttp://hdl.handle.net/11285/636048
dc.description.abstractAgent-based technologies, originally proposed with the aim of assisting human activities, have been recently adopted in industry for automating business processes. Business Process Model and Notation (BPMN) is a standard notation for modeling business processes, that provides a rich graphical representation that can be used for common understanding of processes but also for automation purposes.We propose a normal form of Business Process Diagrams based on Activity Theory that can be transformed to a Causal Bayesian Network, which in turn can be used to model the behavior of activity participants and assess human decision through user agents. We illustrate our approach on an Elderly health care scenario obtained from an actual contextual study.es_MX
dc.language.isoenges_MX
dc.publisherSpringer Verlages_MX
dc.rightsOpen Accesses_MX
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.lcshSciencees_MX
dc.titleA probabilistic BPMN normal form to model and advise human activitieses_MX
dc.typeArtículo / Articlees_MX
dc.identifier.journalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)es_MX
dc.subject.keywordAgent-based systems engineeringes_MX
dc.subject.keywordBPMNes_MX
dc.subject.keywordBayesian networkses_MX
dc.subject.keywordActivity theoryes_MX
dc.identifier.volume9318es_MX
dc.identifier.startpage51es_MX
dc.identifier.endpage69es_MX
dc.contributor.affiliationTecnológico de Monterreyes_MX
dc.subject.lembTurquía / Turkeyes_MX


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