Calibrating Agent-Based Models Using an Improved Genetic Algorithm

Enrique Canessa; Sergio Chaigneau

doi:10.1109/SCCC.2014.12

Calibrating Agent-Based Models Using an Improved Genetic Algorithm

Enrique Canessa, Sergio Chaigneau

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings - 2014 33rd International Conference of the Chilean Computer Science Society, SCCC 2014
Publisher	IEEE Computer Society
Pages	25-29
Number of pages	5
ISBN (Electronic)	9781509004218
DOIs	https://doi.org/10.1109/SCCC.2014.12
State	Published - 1 Sep 2016
Externally published	Yes
Event	33rd International Conference of the Chilean Computer Science Society, SCCC 2014 - Talca, Maule, Chile Duration: 12 Nov 2014 → 14 Nov 2014

Publication series

Name	Proceedings - International Conference of the Chilean Computer Science Society, SCCC
Volume	2016-September
ISSN (Print)	1522-4902

Conference

Conference	33rd International Conference of the Chilean Computer Science Society, SCCC 2014
Country/Territory	Chile
City	Talca, Maule
Period	12/11/14 → 14/11/14

Keywords

Agent-based modelling
calibration
complex adaptive systems
genetic algorithms
relational equivalence
validation

Access to Document

10.1109/SCCC.2014.12

Cite this

Canessa, E., & Chaigneau, S. (2016). Calibrating Agent-Based Models Using an Improved Genetic Algorithm. In Proceedings - 2014 33rd International Conference of the Chilean Computer Science Society, SCCC 2014 (pp. 25-29). Article 7559667 (Proceedings - International Conference of the Chilean Computer Science Society, SCCC; Vol. 2016-September). IEEE Computer Society. https://doi.org/10.1109/SCCC.2014.12

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abstract = "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.",

keywords = "Agent-based modelling, calibration, complex adaptive systems, genetic algorithms, relational equivalence, validation",

author = "Enrique Canessa and Sergio Chaigneau",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 33rd International Conference of the Chilean Computer Science Society, SCCC 2014 ; Conference date: 12-11-2014 Through 14-11-2014",

year = "2016",

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doi = "10.1109/SCCC.2014.12",

language = "English",

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Canessa, E & Chaigneau, S 2016, Calibrating Agent-Based Models Using an Improved Genetic Algorithm. in Proceedings - 2014 33rd International Conference of the Chilean Computer Science Society, SCCC 2014., 7559667, Proceedings - International Conference of the Chilean Computer Science Society, SCCC, vol. 2016-September, IEEE Computer Society, pp. 25-29, 33rd International Conference of the Chilean Computer Science Society, SCCC 2014, Talca, Maule, Chile, 12/11/14. https://doi.org/10.1109/SCCC.2014.12

Calibrating Agent-Based Models Using an Improved Genetic Algorithm. / Canessa, Enrique ; Chaigneau, Sergio.
Proceedings - 2014 33rd International Conference of the Chilean Computer Science Society, SCCC 2014. IEEE Computer Society, 2016. p. 25-29 7559667 (Proceedings - International Conference of the Chilean Computer Science Society, SCCC; Vol. 2016-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Calibrating Agent-Based Models Using an Improved Genetic Algorithm

Abstract

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Keywords

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