Many systems can be modeled as being composed of agents interacting with one another and their environment. As a method, agent based modeling (ABM) can explain phenomena in the biological and social sciences, ranging from evolution to epidemic spread to flocking to cooperation to racial segregation in neighborhoods. Very simple rules governing agent behavior can lead to complex and emergent phenomena. In this course students will use NetLogo to examine and modify well-studied agent based models of complex systems, as well as formulate models of their own.

Course Requirements:

There will be 8 homework assignments. In each assignment, students will be tasked with constructing or modifying an agent based model based on material introduced in lecture or reading. The subjects of the models may include evolution, animal and plant behavior, epidemic spread, social networks, and human interaction. Students will comment on the effects of varying parameters on outcomes of the models.

Intended Audience:

Undergrads interested in a general and flexible tool applicable in many different subjects ranging from the natural to the social sciences, e.g. how to model the spread of disease over human contact networks in epidemiology, and how to model predator-prey dynamics in ecology.

Class Format:

As a DC (Distance due to COVID) course, all aspects of this course will be fully compatible with remote online learning. Class sessions will be a combination of synchronous and asynchronous. Lectures will be live but recorded for posting later. Homework consisting of short answer questions will be submitted to Canvas by a specific date. There will be no exams, but there will be projects that are presented synchronously. Asynchronous presentations will be allowed if requested.