Simplifying Complexity is a podcast that explores the underlying principles of complex systems. Today, we hear from Melanie Moses, Professor in Computer Science at the University of New Mexico. She tells us how she used agent-based models to better understand the spread of COVID in the lungs.
How do you model a complex system? Traditionally we would observe how the system is behaving and create equations to mimic this behaviour, but this doesn't work for complex systems. This is because the interactions between agents in a complex system can significantly impact the system's overall behaviour.
In today's episode, Melanie Moses, Professor of Computer Science at the University of New Mexico, will answer this question. She'll introduce us to agent-based models, which are very different to how we traditionally model systems. More specifically, Melanie will explain how she used agent-based models to understand the spread of coronavirus in the lungs.
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This show is produced in collaboration with Wavelength Creative. Visit wavelengthcreative.com for more information.