Netlogo model "Income distribution inequality and credit risk" courtesy Georgios Papadopoulos, a course participant.

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 using agent-based programming. 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, Complexity Explorer’s massive open online course (MOOC).

Originally offered in 2016, the updated course begins July 9 and runs through October 1. William Rand, an SFI alum and professor of business management at North Carolina State University, will again guide students through the process of creating agent-based models (ABMs), from programming the individual agents to analyzing the collective phenomena that result.   

“Agent-based modeling works forward from an individual agent's rules to observe the pattern that is created,” Rand says. “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 phenomenon 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, and markets. However, students created models in just about every major scientific domain.

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.

The course is offered through SFI’s Complexity Explorer. You can enroll and begin taking the course anytime during the ten-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)