The aim of the course is to familiarize students with the science of complex systems. Students will learn how complexity arises in real scenarios in nature, society and technology. The topics we will discuss include dynamics, chaos, fractals, agent-based modeling, networks and scaling. At the end of the course, students will have knowledge of basic scientific methodologies in the field of Complexity Science and how they are applied in practical settings.

- Elisabeth Lex (website)

- Tomislav Duricic

Course topics include:

- Complex Systems
- Emergence
- Self-organization
- Non-linearity
- Measuring Complexity
- Agent-based Modeling
- Cellular Automata

Students will learn about

- complexity as emerging approach to study systems
- a collection of concepts and theories related to complex systems research
- non-linear thinking

Students will get to know

- practical applications of complexity science
- how to apply complexity science methods

- 18.10.2018: Course Logistics + Motivation
- 08.11.2018: Basic concepts of Complexity
- 15.11.2018: Basic concepts and measuring complexity
- 22.11.2018: Modeling complex systems
- 29.11.2018: Presentation of student topics
- 17.01.2018: Student presentations

The total number of points that can be reached will be 80 (30 for participation + 50 for topic presentation):

- Participation (30 points): questions from previous lecture at the beginning of the next lecture + attendance in class:
- Questionnaires from previous lecture at the beginning of the next lecture
- Attendance in class
- Each student needs to prepare work on a selected topic (50 points):
- You choose a topic out of a set of given topics from the field of complexity science
- Youâ€™ll prepare a presentation (30 min) for your class mates in which you describe the topic and what you have found and learned
- You present in class for your colleagues

The grading scheme is as follows:

- 0-40 points: 5
- 41-50 points: 4
- 51-60 points: 3
- 61-70 points: 2
- 71-80 points: 1