A Novel Modular and Compositional Framework for System Dynamics

Explore a groundbreaking Oxford Seminar presentation by Xiaoyan Li that introduces a next-generation modular and compositional framework for System Dynamics modeling based on Applied Category Theory (ACT). Learn how this innovative approach addresses critical limitations in traditional System Dynamics methodologies, including lack of modularity, inadequate representation of complex relationships, and limited support for model composition and reuse. The seminar begins with a practical application example of a COVID-19 theory-based machine learning model that incorporated Bayesian Particle Filtering algorithms into System Dynamics modeling, which supported decision-making across 17 Canadian jurisdictions during the pandemic. Discover how this ACT-grounded framework enhances flexibility, expressiveness, and applicability of System Dynamics for researchers and practitioners across various domains, from public health and business to environmental management.