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Author (up) Canessa, E.; Chaigneau, S. pdf  doi
  Title Calibrating Agent-Based Models Using a Genetic Algorithm Type
  Year 2015 Publication Studies In Informatics And Control Abbreviated Journal Stud. Inform. Control  
  Volume 24 Issue 1 Pages 79-90  
  Keywords Agent-based modelling; genetic algorithms; calibration; validation; relational equivalence; complex adaptive systems  
  Abstract We present a Genetic Algorithm (GA)-based tool that calibrates Agent-based Models (ABMs). The GA searches through a user-defined set of input parameters of an ABM, delivering values for those parameters so that the output time series of an ABM may match the real system's time series to certain precision. Once that set of possible values has been available, then a domain expert can select among them, the ones that better make sense from a practical point of view and match the explanation of the phenomenon under study. In developing the GA, we have had three main goals in mind. First, the GA should be easily used by non-expert computer users and allow the seamless integration of the GA with different ABMs. Secondly, the GA should achieve a relatively short convergence time, so that it may be practical to apply it to many situations, even if the corresponding ABMs exhibit complex dynamics. Thirdly, the GA should use a few data points of the real system's time series and even so, achieve a sufficiently good match with the ABM's time series to attaining relational equivalence between the real system under study and the ABM that models it. That feature is important since social science longitudinal studies commonly use few data points. The results show that all of those goals have been accomplished.  
  Address [Canessa, Enrique] Univ Adolfo Ibanez, CINCO, Fac Ingn & Ciencias, Vina Del Mar, Chile, Email:;  
  Corporate Author Thesis  
  Publisher Natl Inst R&D Informatics-Ici Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1220-1766 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000351892900009 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 481  
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