CoSMo: a Framework to Instantiate Conditioned Process Simulation Models

arXiv:2303.17879v3 Announce Type: replace-cross
Abstract: Process simulation is gaining attention for its ability to assess potential performance improvements and risks associated with business process changes. The existing literature presents various techniques, generally grounded in process models discovered from event logs or built upon deep learning algorithms. These techniques have specific strengths and limitations. Traditional approaches rooted in process models offer increased interpretability, while those using deep learning excel at generalizing changes across large event logs. However, the practical application of …

abstract algorithms arxiv attention business business process cosmo cs.ai cs.lg deep learning deep learning algorithms event framework improvements literature logs performance process risks simulation type