Agent Based Modeling on Organizational Dynamics of Terrorist Network

Author:

Li Bo1ORCID,Sun Duoyong1,Zhu Renqi1,Li Ze1

Affiliation:

1. College of Information System and Management, National University of Defense Technology, Changsha 410072, China

Abstract

Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Modelling and Simulation

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Promises and pitfalls of computational modelling for insurgency conflicts;The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology;2022-01-24

2. A New Model for Predicting and Dismantling a Complex Terrorist Network;IEEE Access;2022

3. Improving counterfire operations with enhanced command and control structure;Computational and Mathematical Organization Theory;2018-07-16

4. Terrorist Group Behavior Prediction by Wavelet Transform-Based Pattern Recognition;Discrete Dynamics in Nature and Society;2018

5. Empirical research on evolutionary behavior of covert network with preference measurement;Physica A: Statistical Mechanics and its Applications;2017-04

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