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Business Process Simulation with Deep Learning

Manuel Camargo

Collaboration with Marlon Dumas

This project studies the use of generative deep learning models for business process simulation. The main hypothesis is that it is possible to train generative models from business process execution logs using deep learning techniques, which can replicate the behavior of the business process more accurately than existing business process simulation approaches. In addition to exploring this hypothesis, the project investigates how to use and modify such generative models for “what if” simulation based on business process changes.