Our world has an abundance of so-called complex systems. These are typically large collections of connected elements that influence each other. Examples are the brain; society; traffic; the financial system; interacting institutions; climate; ecosystems; interacting atoms or molecules; the World Wide Web. These diverse examples have surprisingly many features in common. As a rule, they show various properties that make complex systems more than the sum of their parts. In this course, we combine examples across physics, the life sciences, socio-economic sciences and humanities with an introduction to basic mathematical tools to learn a complex systems way of thinking.
In recent decades, the science of studying complex systems has started to evolve and mature. It has become clear that a new, more integrated way of thinking is essential for understanding many of the complex challenges that humanity faces. The aim is to derive rules on how the dynamical behaviour of a complex system depends on the combined properties of individual elements, the nature of the interactions between elements, as well as the topology of interactions between elements, in order to understand and predict these systems and control them to have desirable properties. As an example, insight into which features of complex systems generate resilience against perturbations versus which properties enhance the sensitivity of the system and allow it to transition to a different equilibrium state is important for a broad range of questions on, for instance, climate change, social-political change, disruptive innovations, infectious disease emergence and ecosystem collapse.
We focus on the four key aspects of complex systems: emergence, resilience, transitions and predictability and control. We demonstrate how they are recurring concepts in a broad range of areas ranging from the life sciences, social sciences, economics, as well as humanities; and thereby unify them at a deep level. We will stimulate the students to think in terms of these abstract unifying concepts across the diverse disciplines; illustrate the need for mathematical models to study and quantify these properties; and teach the students basic mathematical tools to study the behaviour of the constructed models.
To make the course suitable for most of our participants, the Additional Application Form (only one question) is required for application, you can download it here or make you own form by briefly (max. 150 words) describing your purpose and expectation of following this course, e.g. why you choose “Introduction to Complex Systems” and what you expect to gain from this course.
The aim of the course is: i) to recognise complex systems related to societal, environmental, engineering and scientific problems and to learn their basic features ii) to introduce a complex systems way of thinking and analysis iii) to learn basic mathematical concepts and methods needed for complex system analysis, for example from dynamical systems theory and the theory of networks iv) to get hands-on experience in studying complex systems.
The course consists tutorial lectures and guest lectures from the broadest possible range of topics/fields/problems where complex systems play a role, as well as hands-on computer practice in the afternoons.
Course fee covers lunches, social activity and dinner on Tuesday, drinks and treats during breaks, and a goodie bag from the CCSS.
Housing through: Utrecht Summer School.
Please download the Additional Application Form via https://www.uu.nl/sites/default/files/ccss_additional_application_form.docx or make you own form by briefly (max. 150 words) describing your purpose and expectation of following this course, e.g. why you choose “Introduction to Complex Systems” and what you expect to gain from this course.
For this course you are required to upload the following documents when applying:
Dr. ir. Qingyi Feng | E: Q.Feng@uu.nl | T: 030-2531019