When we observe economic and social systems, gather information, draw inferences, and attempt to predict future outcomes, we are engaged in a process of informal modeling. The workshop introduced IES students to the process of converting such informal models and intuitions into more tangible, formal computational models that users can run, explore, and use to try to change and refine theoretical ideas. The theoretical and methodological basis for this workshop comes from the emerging field of complex systems – a field that studies the dynamics of systems, such as organizations, whose behavior is the consequence of many different interdependent agents, and can be difficult to research using traditional analytical and empirical methods. To investigate the behavior of a natural or social system over time, complex systems research often makes use of computational agent-based models. In particular, agent-based models are used to discover the emergence of macro-level properties from the individual-level actions of the agents, as well as identify leverage points in a social systems – points where a small, local change can have a disproportionate system-level impact.