Calibrating Agent-Based Models Using an Improved Genetic Algorithm

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Resumen

We present an improved GA-based tool that calibrates Agent-Based Models (ABMs). The GA searches through a user-defined set of input parameters to an ABM, delivering values for those parameters so that the output time series of an ABM match the real system's time series to certain precision. The improvements are focused on shortening the computational time that the GA needs to find good solutions. Additionally, one of the new mechanisms prevents the new GA from reaching a certain condition under which the original GA does not converge. The results of experiments show that the improved GA fulfills those goals.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2014 33rd International Conference of the Chilean Computer Science Society, SCCC 2014
EditorialIEEE Computer Society
Páginas25-29
Número de páginas5
ISBN (versión digital)9781509004218
DOI
EstadoPublicada - 1 sep. 2016
Publicado de forma externa
Evento33rd International Conference of the Chilean Computer Science Society, SCCC 2014 - Talca, Maule, Chile
Duración: 12 nov. 201414 nov. 2014

Serie de la publicación

NombreProceedings - International Conference of the Chilean Computer Science Society, SCCC
Volumen2016-September
ISSN (versión impresa)1522-4902

Conferencia

Conferencia33rd International Conference of the Chilean Computer Science Society, SCCC 2014
País/TerritorioChile
CiudadTalca, Maule
Período12/11/1414/11/14

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