A Data Driven Agent Elicitation Pipeline for Prediction Models

Agent-based simulation is a method for simulating complex systems by breaking them down into autonomous interacting agents. However, to create an agent-based simulation for a real-world environment it is necessary to carefully design the agents. In this paper we demonstrate the elicitation of simulation agents from real-world event logs using process mining methods. Collection and processing of event data from a hospital emergency room setting enabled real-world event logs to be synthesized from observational and digital data and used to identify and delineate simulation agents.

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Andrea Burattin

A Data Driven Agent Elicitation Pipeline for Prediction Models

J. Bruntse Larsen, A. Burattin, C.J. Davis, R. Hjardem-Hansen, J. Villadsen

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