Ever wonder how an invasive species spreads? How a social media trend actually develops? How climate change would affect the distribution of trees in a forest?

Computer simulation allows such questions to be explored by modeling the actions and interactions between individual, autonomous agents. Agent-based modeling (ABM) has been used to study everything from economics to biology to political science to business and management. This July, programmers and non-programmers alike can learn to model by enrolling in Introduction to Agent-based Modeling, an online course offered through SFI's Complexity Explorer.

Originally offered in 2016, the updated course begins July 1, 2019, and runs through September 16. Instructor Anamaria Berea will guide students through the process of creating agent-based models (ABMs), from programming the individual agents to analyzing the collective phenomena that result.   

Berea, Associate Research Professor at the University of Central Florida Complex Adaptive Systems Lab, holds dual Ph.D.s in international business and economics (2010) and computational social science (2012), and is a former student of Bill Rand (North Carolina State University), the video instructor and course creator. Berea has a strong background in complexity theory and economics, working at the intersection of economics and computational methods for the past eight years. Her projects include the study of company growth, diffusion of fashions and fads, social media impact on crowd-funding success, the emergence of language and communication in socio-biological networks, geopolitical and science and technology forecasting, recommender systems for students applying to college, mass media sales forecasting, simulation of conflicts in Afghanistan-Pakistan area and many more. 

“Agent-based modeling works forward from an individual agent's rules to observe the pattern that is created,” says Rand. “This makes ABM a natural method for exploring complex systems. Students will be able to build and construct their own agent-based models to understand phenomena of interest to themselves, and to analyze the results of those models in a rigorous, scientific fashion so they can make clear generalizations of the results.” Some general topics from the initial iteration of the class stood out: social, people, networks, behavior, biology, ecology, and markets. However, students created models in just about every major scientific domain. Check out the top 2018 model assignments here.

The course explores why agent-based modeling is a powerful method for understanding complex systems, and what kinds of complex systems are amenable to this type of analysis. Students will learn why and when to use agent-based models, and then build their own simulations from the ground up. Many students in the initial class claimed to have never done any programming before, but were able to build models on a wide variety of phenomena, including the domains of organizational science, human interaction, population ecology, disease spread, political science, finance, and others.

The course’s first module will be open to everyone, and a modest tuition is requested for those interested in continuing through the course and receiving a certificate of completion. Video materials, quizzes, and homework from the course will be freely available after the course is closed.

You can enroll and begin taking the course anytime during the 11-week course.  For students wanting to get a head start, Rand recommends downloading NetLogo 6.0.1 and playing around with it. Or going through the three tutorials included in the NetLogo documentation. For those even more interested, Rand has written a textbook on the subject: An Introduction to Agent-Based Modeling by Wilensky and Rand.

The course is a continuation of the successful massive open online course (MOOC) series that began with SFI External Professor Melanie Mitchell’s Introduction to Complexity.

For more information, or to enroll, visit the Introduction to Agent-Based Modeling course page at SFI's Complexity Explorer.

Watch an introduction to the course in this video featuring Bill Rand (4.5 minutes)