VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Complex Adaptive Systems
Last Updated: 2026-02-05 15:19:14
Abstract
spatio-temporal structure formation, self-organization, multi-agent systems and cellular automata, structure and dynamics of networks theory, evolutionary processes
Objective
The course provides a broad overview of concepts and methods used in the field of complex adaptive systems. Methods of dynamical systems and statistical physics provide the tools for formally describing and analysing these systems. The collective dynamics are illustrated by means of computer simulations, mainly using multi-agent approaches.
Content
What do gregarious insects, neurons, or human voters have in common? They form complex systems with multiple interacting components (agents). In complex systems, the behavior cannot be simply inferred from the behavior of the agents. Nonlinear feedback processes together with specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale. In complex adaptive systems, the agents are able to adapt to changing external or internal conditions. This may lead to even more complex dynamics and, together with concepts of evolutionary optimization, provides a framework of evolutionary processes. The course presents this cutting-edge research area from different perspectives. In the first part, the basic concepts of nonlinear dynamical systems are introduced and applied to spatio-temporal structure formation. In particular the emergence of patterns in physico-chemical and biological systems is discussed. In the second part, two different agent-based frameworks for modeling complex systems are introduced: Brownian agents and cellular automata. Discussed examples range from opinion dynamics and evolutionary game theory to population dynamics. In the third part, the focus is on the structural and dynamical features of networks, with an emphasis on random Boolean networks and catalytic networks. Applications cover prebiotic evolution as well as social and economic networks where the interaction between nodes evolves over time.
Resources
Lecture Notes
The lecture slides are provided as handouts - including notes and literature sources - on thehomepage of the Chair of Systems Design.
Literature
See handouts.
General Information
- Language
- English
- Levels
- DS , MSC
- Frequency
- Yearly recurring
Examination
- Type
- end-of-semester examination
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Complex Adaptive Systems |
|
2 h weekly |
| exercise | Complex Adaptive Systems |
|
1 h weekly |
Offered In
-
Mathematics, Computational Science and Engineering (Mathematics, Physics Those who want to register for elective courses in the diploma degree programme im Mathematics, should select these from the range of courses of the Master programme in Mathematics. Those who want to register for core subject and elective courses in the diploma degree programme in Physics, should select these from the range of courses of the Master programme in Physics (Core Courses: Theoretical Physics, Core Courses: Experimental Physics, Electives: Physics and Mathematics). The same holds for seminars and semester projects and papers.)
-
-
-
-
-
-
Application Area (only necessary for MSc in Applied Mathematics)
-
-
-