Course Description

Description: 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 misinformation 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, patterns of human behavior, as well as the operation of social groups, natural environments, organizations and economies, and science itself. 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 seminar is designed to present and discuss the history, methodology and impact of complex systems; we cover key literature as well as recent advances in the field.

Course Evaluation

Students are expected to read and annotate the materials presented, as well as present several of the key readings. Students will also work on a term project or paper. Participation and Discussion: 15%; Lead Discussions: 25%; Term Paper/Project: 60%.

Office Hours

Luis Rocha: Wednesdays 8:30 - 11:00 AM, Online

Course Materials and Readings

  1. Cybernetics and the Information Turn
  2. Systems Science, Organization, Prediction, and Limits
  3. Self-Organizing Systems
  4. Second-Order Cybernetics
  5. Organization of Complex Systems
  1. Towards a practice of Complex Systems: Interdisciplinarity and Limits
  2. Evolutionary Systems
  3. Networks, Systems Biology, and Neo-Cybernetics themes

Last Modified: April 15th , 2021