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Adapting Workflows to Intelligent Environments

Hartmann, Melanie ; Ständer, Marcus ; Uhren, Victoria (2011)
Adapting Workflows to Intelligent Environments.
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Intelligent environments aim at supporting the user in executing her everyday tasks, e.g. by guiding her through a maintenance or cooking procedure. This requires a machine processable representation of the tasks for which workflows have proven an efficient means. The increasing number of available sensors in intelligent environments can facilitate the execution of workflows. The sensors can help to recognize when a user has finished a step in the workflow and thus to automatically proceed to the next step. This can heavily reduce the amount of required user interaction. However, manually specifying the conditions for triggering the next step in a workflow is very cumbersome and almost impossible for environments which are not known at design time. In this paper, we present a novel approach for learning and adapting these conditions from observation. We show that the learned conditions can even outperform the quality as conditions manually specified by workflow experts. Thus, the presented approach is very well suited for automatically adapting workflows in intelligent environments and can in that way increase the efficiency of the workflow execution.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2011
Autor(en): Hartmann, Melanie ; Ständer, Marcus ; Uhren, Victoria
Art des Eintrags: Bibliographie
Titel: Adapting Workflows to Intelligent Environments
Sprache: Deutsch
Publikationsjahr: 2011
Verlag: IEEE
Buchtitel: Proceedings of the 2011 Seventh International Conference on Intelligent Environments
Kurzbeschreibung (Abstract):

Intelligent environments aim at supporting the user in executing her everyday tasks, e.g. by guiding her through a maintenance or cooking procedure. This requires a machine processable representation of the tasks for which workflows have proven an efficient means. The increasing number of available sensors in intelligent environments can facilitate the execution of workflows. The sensors can help to recognize when a user has finished a step in the workflow and thus to automatically proceed to the next step. This can heavily reduce the amount of required user interaction. However, manually specifying the conditions for triggering the next step in a workflow is very cumbersome and almost impossible for environments which are not known at design time. In this paper, we present a novel approach for learning and adapting these conditions from observation. We show that the learned conditions can even outperform the quality as conditions manually specified by workflow experts. Thus, the presented approach is very well suited for automatically adapting workflows in intelligent environments and can in that way increase the efficiency of the workflow execution.

ID-Nummer: TUD-CS-2011-0220
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik > Telekooperation
20 Fachbereich Informatik
Hinterlegungsdatum: 31 Dez 2016 12:59
Letzte Änderung: 15 Mai 2018 12:01
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