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Updated: Jun 2, 2025

Surrogate Model Development for Digital Experiments in Welding
Published on: March 28, 2025
Optimal control of agent-based models via surrogate modeling
Luis L Fonseca1, Lucas Böttcher1,2, Borna Mehrad1
1Laboratory for Systems Medicine, Department of Medicine, University of Florida, Gainesville, Florida, United States of America.
Abstract:
This paper describes and validates an algorithm to solve optimal control problems for agent-based models (ABMs). For a given ABM and a given optimal control problem, the algorithm derives a surrogate model, typically lower-dimensional, in the form of a system of ordinary differential equations (ODEs), solves the control problem for the surrogate model, and then transfers the solution back to the original ABM. It applies to quite general ABMs and offers several options for the ODE structure, depending on what information about the ABM is to be used. There is a broad range of applications for such an algorithm, since ABMs are used widely in the life sciences, such as ecology, epidemiology, and biomedicine and healthcare, areas where optimal control is an important purpose for modeling, such as for medical digital twin technology.
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