POWL: Partially Ordered Workflow Language (Extended Abstract)

POWL: Partially Ordered Workflow Language (Extended Abstract)

Humam Kourani, Sebastiaan van Zelst

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
Sister Conferences Best Papers. Pages 8427-8432. https://doi.org/10.24963/ijcai.2024/935

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.
Keywords:
Data Mining: General
Multidisciplinary Topics and Applications: General