![]() The ask which follows calculates the population density of each patch, and colours it appropriately. Here the calls to gis:apply-coverage copy values from the GIS country dataset to the named patch variables. Set pcolor (scale-color red population-density 400 0 ) ] Set population-density (population / area) [ Colour patch according to population density Gis:apply-coverage countries-dataset "CNTRY_NAME" country-name Gis:apply-coverage countries-dataset "SQKM" area Show "Loading patches." gis:apply-coverage countries-dataset "POP_CNTRY" population Loading the GIS data is much like Uri Wilensky’s “GIS General Examples” model (specific details will be given later), while the following procedure sets up the population density data in the patches: to setup-gis The same approach, with different GIS datasets, allows models of individual countries, states, or cities, with populations determined by GIS data on, for example, counties or suburbs. Pawel Sobkowicz, “ Extremism without extremists: Deffuant model with emotions” ( ).Constructing agent populations in this way allows agents to have country-dependent behaviour. He is currently working with two academic teams applying computer modeling to research on “Fake News” and Intergenerational Obesity. He developed and teaches a course, “Modeling & Simulation with R & Python” as well as teaching the program’s course in Agent Based Modeling. candidate in the Systems Science program at Portland State University, working under Dr. Instructor Biography:ĭale Frakes is a Ph.D. We will be using NetLogo ( ) and ideally it will already be installed on the attendee's computer before the session begins. While spectators are welcome, this instructor-led tutorial is designed to be a hands-on effort and attendees will get the most out of it by working through the exercises.
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