Validating Game-Theoretic Models of Terrorism: Insights from Machine Learning

James Bang, Atin Basuchoudhary and Aniruddha Mitra
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Aniruddha Mitra: Economics Program, Bard College, Annandale-On-Hudson, NY 12504, USA

Games, 2021, vol. 12, issue 3, 1-20

Abstract: There are many competing game-theoretic analyses of terrorism. Most of these models suggest nonlinear relationships between terror attacks and some variable of interest. However, to date, there have been very few attempts to empirically sift between competing models of terrorism or identify nonlinear patterns. We suggest that machine learning can be an effective way of undertaking both. This feature can help build more salient game-theoretic models to help us understand and prevent terrorism.

Keywords: machine learning; terrorism; game theory (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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