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Calibrating a System Dynamic Model Within an Integrative Framework to Test Foreign Policy Choices

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Date Issued:
2017
Abstract/Description:
Political science uses international relations (IR) theory to explain state-actor political behavior. Research suggests that this theoretical framework can inform a predictive model incorporating features of systems dynamics (SD) and agent based (AB) modeling. The Foreign Policy Model (ForPol) herein applies Alexander Y. Lubyansky's (2014) SD model for macro-political behavior to represent behaviors between real systems and mental models. While verifying and validating the resulting SD/AB/IR holistic model requires an extensive comprehensive research agenda, the present work will take a closer examination at input parameter calibration and conducting typical runs of the SD portion of the model as a first step in the testing, verification and validation process of the proposed integrative model. This thesis proposes incorporating an AB paradigm drawn from work by Claudio Cioffi-Revilla (2009), Edward P. MacKerrow (2003), David L. Rousseau (2006), Joshua M. Epstein and Robert Axtell (1996) as a future hybrid extension.The model applies a SD approach for the modeling of macro-political aggregate behavior. Therefore, the deep analysis of the SD portion of ForPol is modeled and calibrated in Vensim, using empirical data from the 1967 Arab-Israeli Six Day War as a pilot. Interactions within the model actualize Choucri, et. al. (2006), definition of state stability and agent behavior aspects of Cioffi-Revilla's (2009) SimPol polity model. Following calibration results discussion, the present work closes with consideration of future research directions.
Title: Calibrating a System Dynamic Model Within an Integrative Framework to Test Foreign Policy Choices.
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Name(s): Kavetsky, Carlos, Author
Morrow, Patricia Bockelman, Committee Chair
Wiegand, Rudolf, Committee CoChair
Wu, Annie, Committee Member
Akbas, Ilhan, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2017
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Political science uses international relations (IR) theory to explain state-actor political behavior. Research suggests that this theoretical framework can inform a predictive model incorporating features of systems dynamics (SD) and agent based (AB) modeling. The Foreign Policy Model (ForPol) herein applies Alexander Y. Lubyansky's (2014) SD model for macro-political behavior to represent behaviors between real systems and mental models. While verifying and validating the resulting SD/AB/IR holistic model requires an extensive comprehensive research agenda, the present work will take a closer examination at input parameter calibration and conducting typical runs of the SD portion of the model as a first step in the testing, verification and validation process of the proposed integrative model. This thesis proposes incorporating an AB paradigm drawn from work by Claudio Cioffi-Revilla (2009), Edward P. MacKerrow (2003), David L. Rousseau (2006), Joshua M. Epstein and Robert Axtell (1996) as a future hybrid extension.The model applies a SD approach for the modeling of macro-political aggregate behavior. Therefore, the deep analysis of the SD portion of ForPol is modeled and calibrated in Vensim, using empirical data from the 1967 Arab-Israeli Six Day War as a pilot. Interactions within the model actualize Choucri, et. al. (2006), definition of state stability and agent behavior aspects of Cioffi-Revilla's (2009) SimPol polity model. Following calibration results discussion, the present work closes with consideration of future research directions.
Identifier: CFE0006750 (IID), ucf:51848 (fedora)
Note(s): 2017-08-01
M.S.
Engineering and Computer Science, Dean's Office GRDST
Masters
This record was generated from author submitted information.
Subject(s): System Dynamic
Agaent-Based
Political Simulation
Input Parameter Calibration
Foreign Policy
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0006750
Restrictions on Access: public 2017-08-15
Host Institution: UCF

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