Designing and Constructing Models with Multi-Agent Languages
This course will begin with an introduction to the multi-agent language NetLogo. Students will design and implement several NetLogo models and analyze their behavioral regimes. Students will also learn to build models of interaction on social networks (or other types of networks). We will cover methodology for verifying, validating and replicating agent-based models and comparisons with systems dynamics and equation-based models. NetLogo comes with many extensions that support a variety of additional features. Students can use these extensions to create specialized models, such as complex networks, real-time data extraction, data mining, connections to physical devices, etc.. Students will also have an opportunity to explore existing and create their own participatory simulations using the HubNet architecture as well as exploring connecting real world sensors and motors to models. Students can also explore multi-level agent-based modeling in which hundreds or thousands of models are connected with NetLogo’s LevelSpace extension.
Prerequisites & course information
Prerequisites: Comp_sci PhDs or Comp_Eng PhDs or TSB PhDs or CS LS PhDs or Consent of instructor.
Sources
- Course catalogue ↗2026–2027