Fantastic Simulation of Social Systems and Where to Find Them
Post-doctoral researcher at Università Carlo Cattaneo - LIUC, where he is the holder of the Dynamical System Design course. He studies how to apply and extend simulation computational methodologies to different kinds of complex social systems.
He is also a research fellow at HD-LAB - Healthcare Datascience Lab, where he is involved in the use of computational methods to study and support the Italian healthcare system
This presentation examines how simulation can provide insights into complex social systems across four areas: emergency care management, epidemiological modeling, historical analysis, and other ongoing research projects of the speaker. In the emergency care context, a gravity model incorporating factors like travel distance, hospital capacity, and patient severity is used to predict hospital choice, forming the basis for an agent-based model (ABM) of the entire emergency care system. Limitations in current overcrowding metrics and potential network analysis solutions are also discussed. An epidemiological adaptation of the El Farol Bar problem integrates social dynamics and contagion processes to explore how decision-making affects public health, identifying conditions under which behavioral cycles emerge. Additionally, reinforcement learning is employed to model adaptive policy responses. Historical studies include a dynamical network simulation of Iron Age trade and an ABM of city-state success, with implications for real-world historical scenarios. The presentation concludes with ongoing projects on ski resorts, innovation markets, and circular economy models.
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