What are the essential theoretical background and technical skills needed to conceptualize, build, and analyze an agent-based model? Nick Magliocca, Assistant Research Professor at the National Socio-Environmental Synthesis Center (SESYNC), led a Spatial Agent-Based Modeling short course in December to help researchers develop that expertise. With Kelly Hondula, Quantitative Researcher and Computer Programmer, and Ian Carroll, Data Science Instructor, the course guided participants through the basic phases of the agent-based modeling research process. The syllabus and lecture materials are publicly available on our website here and highlighted below. Of special interest are the lecture on "What are agent-based models (ABMs)?" and the RNetLogo tutorial.
Lectures
Lecture: What are socio-environmental (S-E) systems?
Lecture: What are agent-based models (ABMs)?
Lecture: Introduction to "building-blocks" of ABMs
Lecture: Introduction to spatially-explicit ABMs
Lecture: Introduction to model calibration, sensitivity analysis, and evaluation
Tutorials
Tutorial: NetLogo Basics
Tutorial: Programming in NetLogo
Tutorial: Introduction to Code Versioning with Git
Tutorial: Use R to analyze NetLogo simulations
Tutorial: GIS and NetLogo