Andrea Burattin

Associate Professor
Technical University of Denmark


A Data Driven Agent Elicitation Pipeline for Prediction Models

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

In Proceedings of PODS4H 2019; Vienna, Austria; September 2019.

General rights

Copyright and moral rights for the publications made accessible in the public website are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Latest website update: 17 April 2024.