Friday, March 15, 2024 | 10:00 am (CET) | Room: S.2.69 | Universität KlagenfurtMatteo Zavatteri | Assistant Professor in computer science at the Department of Mathematics of University of Padua, Italy
Abstract: A recent direction in Business Process Management studied methodologies to control the execution of Business Processes under several sources of uncertainty in order to always get to the end by satisfying all constraints. Current approaches encode business processes into temporal constraint networks or timed game automata in order to exploit their related strategy synthesis algorithms. However, the proposed encodings can only synthesize single-strategies and fail to handle loops. To overcome these limits I will discuss a recent approach based on supervisory control. The approach considers structured business processes with resources, parallel and mutually exclusive branches, loops, and uncertainty. I will discuss an encoding into finite state automata and prove that their concurrent behavior models exactly all possible executions of the process. After that, I will introduce tentative commitment constraints as a new class of constraints restricting the executions of a process. Finally, I will discuss a tree decomposition of the process that plays a central role in modular supervisory control.
Bio: Matteo Zavatteri is assistant professor in computer science at the Department of Mathematics of University of Padua, Italy. He received a master degree in engineering and computer science and a Ph.D. in computer science from University of Verona (ITALY).
His research interests are in the fields of formal methods, discrete event systems, supervisory control, temporal reasoning, artificial intelligence, and business process management. Currently he works in the iNEST (Interconnected Nord-Est Innovation Ecosystem) project, which is a project supported with 110M€ by the National Recovery and Resilience Plan, funded by the European Union in the NextGenerationEU plan. In such a project he develops neuro-symbolic approaches for digital twins.
Mathematics of University of Padua, Italy. He received a master degree in engineering and computer science and a Ph.D. in computer science from University of Verona (ITALY).
His research interests are in the fields of formal methods, discrete event systems, supervisory control, temporal reasoning, artificial intelligence, and business process management. Currently he works in the iNEST (Interconnected Nord-Est Innovation Ecosystem) project, which is a project supported with 110M€ by the National Recovery and Resilience Plan, funded by the European Union in the NextGenerationEU plan. In such a project he develops neuro-symbolic approaches for digital twins.
