This course, "Introduction to Complexity Science," delves into the intricate features of complex systems and their ubiquitous presence in our interconnected world. Through a multidisciplinary approach, participants will explore the resilience, robustness, and sustainability of these systems, acquiring a deep understanding of their essential dynamics.
This course, offered by Nanyang Technological University, Singapore, provides a unique opportunity to develop a sophisticated understanding of complexity science and its practical implications in diverse contexts.
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The course modules cover a broad spectrum of topics, including an introduction to complex systems, robustness, resilience, sustainability, regime shifts, tipping points, agent-based modeling, and static complex networks. Participants will gain practical insights through comprehensive lectures and practical applications.
The course begins with an overview and introduction to complex systems, examining the behavior of scale-free networks and the implications of complexity in society, such as pandemics and crime.
Participants will explore the concepts of robustness, resilience, and sustainability, considering real-world examples and the design and control of swarm dynamics.
This module delves into regime shifts and tipping points, including criticality, Landau theory, and forecasting methods, providing a comprehensive understanding of the dynamics of complex systems.
Participants will gain insights into agent-based modeling, including validation, calibration, and its use for policy assessment, culminating in the exploration of Schelling's Segregation Model.
This module focuses on static complex networks, covering random networks, scale-free networks, robustness, and practical sessions using Python, culminating in the final assessment.
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