5 papers
An Infectious Disease Spread Simulation Based on Large Language Model Decision Making
Yonchanok Khaokaew, Ruochen Kong, Andreas Zufle +6
Modelling individual decision-making during infectious disease outbreaks is crucial for understanding behavioural dynamics and informing effective public health interventions. Prio…
SF-LIFE: A Large-Scale Simulated Movement Dataset for the San Francisco Bay Area
Chanuka Algama, Taylor Anderson, Henrique Ferraz de Arruda +14
We introduce SF-LIFE, a large-scale simulated movement dataset designed to accelerate research in transportation, mobility, and machine learning. The dataset contains 3,024,000,000…
All Models Are Wrong, But Can They Be Useful? Lessons from COVID-19 Agent-Based Models: A Systematic Review
Emma Von Hoene, Sara Von Hoene, Szandra Peter +9
The COVID-19 pandemic prompted a surge in computational models to simulate disease dynamics and guide interventions. Agent-based models (ABMs) are well-suited to capture population…
Evaluating the Bias in LLMs for Surveying Opinion and Decision Making in Healthcare
Yonchanok Khaokaew, Flora D. Salim, Andreas Züfle +5
Generative agents have been increasingly used to simulate human behaviour in silico, driven by large language models (LLMs). These simulacra serve as sandboxes for studying human b…
Function and form of U.S. cities
Sandro M. Reia, Taylor Anderson, Henrique F. Arruda +4
The relationship between urban form and function is a complex challenge that can be examined from multiple perspectives. In this study, we propose a method to characterize the urba…