Systems Thinking

We deal with a plethora of complex problems, such as why inequality is increasing? Do racial teams have greater decision-making abilities?, How can we predict the outcomes of elections?, and many others. In order to confront such complexity, we need to use models. Whether you work with science, business, policymaking, or even art, you will confront complex problems in different forms and contexts. Thinking in systems will significantly help you comprehend and make the best use of data available for you to predict, understand, and develop the systems you are working with.
The course offers an introduction to modeling complex systems. It highlights different modeling approaches and several examples to study. Furthermore, the course introduces interactions systems as a key component of complex systems and explains how these can influence the emergent behaviors.

After successful completion of this course students are expected to be able to:

• Model and analyze complex systems
• Develop a background on different approaches for modeling complex systems (e.g. agent-based modelling and system dynamics)
• Understand interaction models (e.g. social networks) and their role in complex systems
• Identify complexity in own research problems

Assumed Knowledge:
Affinity with modeling and simulation