Advances in surrogate modeling for biological agent-based simulations: trends, challenges, and future prospects

Agent-based modeling (ABM) is a powerful computational approach for studying complex biological and biomedical systems, yet its widespread use remains limited by significant computational demands. As models become increasingly sophisticated, the number of parameters and interactions rises rapidly, e...

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Bibliographic Details
Published in:Journal of mathematical biology 2026-01, Vol.92 (1), p.6, Article 6
Main Authors: Norton, Kerri-Ann, Bergman, Daniel, Jain, Harsh Vardhan, Jackson, Trachette
Format: Article
Language:English
Subjects:
Accuracy
Agent-based models
Animals
Biology
Biomedical materials
Calibration
Computational Biology
Computer applications
Computer Simulation
Growth models
Humans
Learning algorithms
Machine Learning
Mathematical Concepts
Models, Biological
Neural networks
Oncology
Parameter estimation
Parameter sensitivity
Parameter uncertainty
Partial differential equations
Sensitivity analysis
Statistical analysis
Systems Biology - trends
Uncertainty
Uncertainty analysis
Citations: Items that this one cites
Online Access:Get full text
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