{"type":"ScholarlyArticle","title":"POWL: Partially Ordered Workflow Language (Extended Abstract)","authors":[{"name":"Humam Kourani","slug":"humam-kourani","given":"Humam","family":"Kourani","affiliation":"Fraunhofer Institute for Applied Information Technology FIT , Sankt Augustin , Germany; RWTH Aachen University , Aachen , Germany"},{"name":"Sebastiaan van Zelst","slug":"sebastiaan-van-zelst","given":"Sebastiaan","family":"van Zelst","affiliation":"Celonis Labs GmbH , Munich , Germany"}],"abstract":"Processes in real-life scenarios tend to inherently establish partial orders over their constituent activities. This makes partially ordered graphs viable for process modeling. While partial orders capture both concurrent and sequential interactions among activities in a compact way, they fall short in modeling choice and cyclic behavior. To address this gap, we introduce the Partially Ordered Workflow Language (POWL), a novel language for process modeling that combines traditional hierarchical modeling languages with partial orders. In a POWL model, sub-models are combined into larger ones either as partial orders or using control-flow operators that enable the representation of choice and loop structures. This integration of hierarchical structure and partial orders not only offers an effective solution for process modeling but also provides quality guarantees that make POWL particularly suitable for the automated discovery of process models.","doi":"10.24963/ijcai.2024/935","url":"https://ijcai.org/proceedings/2024/935","pdf":"https://ijcai.org/proceedings/2024/0935.pdf","markdown":"https://ijcai.org/proceedings/2024/935.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/935","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Sister Conferences Best Papers","track":"Sister Conferences Best Papers","number":935,"pages":{"first":8427,"last":8432},"keywords":["Multidisciplinary Topics and Applications: General","Data Mining: General"],"videos":[],"references":[{"position":1,"raw":"[Berti and van der Aalst, 2019] Alessandro Berti and Wil M. 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