Using machine learning as a surrogate model for agent-based simulations.

In this proof-of-concept work, we evaluate the performance of multiple machine-learning methods as surrogate models for use in the analysis of agent-based models (ABMs). Analysing agent-based modelling outputs can be challenging, as the relationships between input parameters can be non-linear or eve...

Full description

Saved in:
Bibliographic Details
Main Authors: Claudio Angione, Eric Silverman, Elisabeth Yaneske
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0263150&type=printable
Tags: Add Tag
No Tags, Be the first to tag this record!