Course Description

Description:The course deals with the foundations of Systems Science, as well as current advances in Complex Networks and Systems which is the modern expression of this interdisciplinary field. A complex system is any system featuring a large number of interacting components (agents, processes, etc.) whose aggregate activity is nonlinear (not derivable from the summations of the activity of individual components) and typically exhibits hierarchical self-organization under selective pressures. The networks of interactions that comprise such systems can be studied separately from or together with the multivariate dynamics that define them. In the former case, the focus is the graph structure of networks which is typically pursued in Network Science, whereas dynamical systems theory focuses on the latter. Understanding networked complex systems is key to solving some of the most vexing problems confronting humankind, from discovering how thoughts and behaviors arise from dynamic brain connections, to detecting and preventing the spread of epidemics or unhealthy behaviors across a population. But the study of complex systems requires an understanding of both structure and dynamics which often interact in non-separable multiple levels where information, selection, and collective dynamics operate. Indeed, modeling network interactions among variables operating at multiple scales is an essential capability for effective interventions in complex systems---such as the dynamic web of cellular processes and genetic regulation, the intricate wiring of the brain, as well as patterns of human and social behavior involved in disease. Across all these systems, mapping, analyzing, modeling, and visualizing underlying networks are indispensable steps toward understanding how they work. The sciences of complexity are also necessarily based on interdisciplinary research so that teams of scientists can most effectively approach both the general characteristics of all these systems as well as the specific methodologies required to measure and model them.

Aims: This course is designed to introduce and discuss the history, methodology and impact of complex systems science; we cover key literature, recent advances in the field, and introduce useful computational techniques in the field. We will study concepts such as Information, General Systems Theory, Networks, Modeling, Multi-Level Complexity, as well as their impact on science and society. The course will also attempt to define and understand what systems thinking can bring to science and society.


Lecture Outline

Course Evaluation

Office Hours

Luis M. Rocha: Tuesdays: 9:00 - 11:30am, EB-S4, EB-C3, or Online.

Vision (Xin) Wang (TA): Tuesdays 4-5pm, Wednesdays 12:30-2:30pm, and Thursdays 9:00-11:00am, EB-K1, Online, or by appointment.

Course Materials and Readings

Readings, available on line, library reserve or Brightspace

  1. Cybernetics and the Information Turn
  2. From Cybernetics to Systems Science
  3. Organization of Complex Networks and Systems
  4. Towards a practice of Systems Science: Interdisciplinarity and multi-level complexity

Last Modified: December 7th, 2023