HAMED, Imen and CHARRAD, Malika, 2015. Recognizing Information Spreaders in Terrorist Networks: 26/11 Attack Case Study. In: BELLAMINE BEN SAOUD, Narjès, ADAM, Carole and HANACHI, Chihab (eds.), Information Systems for Crisis Response and Management in Mediterranean Countries. Online. Cham: Springer International Publishing. p. 27–38. Lecture Notes in Business Information Processing. ISBN 978-3-319-24398-6. [Accessed 5 February 2024]. ILACHINSKI, Andrew, 2005. Self-organized terrorist-counterterrorist adaptive coevolutions, part 1: a conceptual design. CENTER FOR NAVAL ANALYSES ALEXANDRIA VA. ILACHINSKI, Andrew, 2009. EINSTein. In: Artificial Life Models in Software. Springer. p. 259–315. ILACHINSKI, Andrew, 2012. Modelling insurgent and terrorist networks as self-organised complex adaptive systems. International Journal of Parallel, Emergent and Distributed Systems. 2012. Vol. 27, no. 1, p. 45–77. MESJASZ, Czeslaw, 2015. Complex Systems Studies and Terrorism. In: FELLMAN, Philip Vos, BAR-YAM, Yaneer and MINAI, Ali A. (eds.), Conflict and Complexity. Online. New York, NY: Springer New York. p. 35–71. Understanding Complex Systems. ISBN 978-1-4939-1704-4. [Accessed 5 February 2024].
Self-Organized Terrorist-Counterterrorist Adaptive Coevolutions
SOTCAC uses autonomous, intelligent agents to represent the components of coevolving terrorist and counterterrorist networks.
Finally, SOTCAC builds upon the multiagent-modeling technologies underlying both the EINSTein and SCUDHunt simulations, recently developed at the Center for Naval Analyses (CNA).
EINSTein and SCUDHunt are agent-based simulations of ground combat and shared Situational Awareness in a wargame context, respectively. Those portions of these models that bear directly on SOTCAC’s design are described in the main text of this paper. For additional details, see A. Ilachinski, EINSTein, CRM 2239, 2000, and P. Perla, et al., Using Gaming and Agent Technology to Explore Joint Command and Control Issues, CRM 7164, 2002.
SOTCAC uses adaptive agents to describe the self-organized, emergent behavior of terrorist networks – conceived as complex adaptive systems – on three interrelated dynamical levels:
1. Dynamics on networks, in which notional terrorist agents process and interpret information, search and acquire resources, and adapt to other agents’ actions;
2. Dynamics of networks, in which the terrorist network itself is a fully dynamic, adaptive entity; and whose agents build, maintain, and modify the network’s local (and therefore, collectively, its global) topology; and
3. Dynamics between networks, in which the terrorist network and counterterrorist network mutually coevolve; the terrorist network’s “goal” is to achieve the critical infrastructure (of manpower, weapons, financial resources, and logistics) required to strike, while the counterterrorist network’s mission is to prevent the terrorist network from achieving its Goal. [⇒ Ends Planning]
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ILACHINSKI, Andrew, 2005. Self-Organized Terrorist- Counterterrorist Adaptive Coevolutions, Part I: A Conceptual Design.
BASE, MAXWELL AIR FORCE, 2022. IN℡LIGENCE, SURVEILLANCE, AND RECONNAISANCE CONSIDERATIONS FOR NATIONAL SECURITY. 2022. pdf 
[Accessed 5 February 2024].
CIOFFI-REVILLA, Claudio, 2017. Agent-Based Computational Modeling and International Relations Theory: Quo Vadis? In: Oxford Research Encyclopedia of Politics. Online. Available from: https://oxfordre.com/politics/display/10.1093/acrefore/9780190228637.001.0001/acrefore-9780190228637-e-535 [Accessed 5 February 2024].
ORMROD, David, 2017. Cyberspace Weaponisation: Modelling Cyber-Effects and their Impacts on Mission Success, Human Factors and Kinetic Outcomes in the Tactical Land Combat Environment. PhD Thesis. UNSW Sydney. page [Accessed 5 February 2024]. r.CyberspaceWeaponisation.Ormrod