GeneGenetic algorithms try to solve a computational problem following some principles of organic evolution. This model has didactic purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the possible answers to solve the problem are represented by agents, that in logo programming environment are usually known as “turtles”.
This model explores a social mechanism that links the reversal of the gender gap in education with changing patterns in relative divorce risks in 12 European countries.
We explore how dynamic processes related to socioeconomic inequality operate to sort students into, and create stratification among, colleges.
The purpose of this model is to investigate mechanisms driving the geography of educational inequality and the consequences of these mechanisms for individuals with varying attributes and mobility.