Business processes are usually modeled at a high level of abstraction, while the analysis of their run-time behavior through process mining techniques is based on low-level events recorded in an event log. In this scenario, it is difficult to discover the relationship between the process model and the run-time behavior, and to check whether the model is actually a good representation for that behavior. In this work, we introduce an approach that is able to capture such relationship in a hierarchical model. In addition, through a combination of process mining and agent-based simulation, the approach supports the improvement of the process model so that it becomes a better representation for the behavior of agents in the process. For this purpose, the model is evaluated based on a set of metrics. We illustrate the approach in an application scenario involving a purchase process.
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