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...
Main Authors: | Claudio Angione, Eric Silverman, Elisabeth Yaneske |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2022-01-01
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Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0263150 |
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