Andrea Burattin, Ph.D.

Associate Professor, Technical University of Denmark

A Data Driven Agent Elicitation Pipeline for Prediction Models

Abstract

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.

Paper Information and Files

Published in Proceedings of PODS4H 2019; Vienna, Austria; September 2019.