Adversarial Behavior in Complex Adaptive Systems: An Overview of ICST’s Research on Competitive Adaptation in Militant Networks

Abstract

There is widespread agreement among scholars and practitioners that the counterterrorism literature suffers from a lack of primary-source field research. The absence of solid ethnographic research has yielded studies that suffer from a lack of rigorous analysis and often result in opinion masquerading as analysis. The lack of field research is also due to a failure to integrate ethnographic research into modeling efforts, as well as a failure more broadly to appreciate the significance of ethnographically valid data in human, social, cultural, and behavioral studies in a systematic investigation of terrorist behavior. The project briefly outlined in this paper seeks to redress this deficiency by combining the strengths of ethnographic field research (collected by social scientists at Penn State) with the sophisticated modeling capabilities of computer scientists (at Carnegie Mellon University). Specifically, we are analyzing data from interview transcripts, news reports, and other open sources concerning the militant activist group Al-Muhajiroun and the terrorist groups Provisional Irish Republican Army (PIRA) and Revolutionary Armed Forces of Colombia (FARC). Using competitive adaptation as a comparative organizational framework, this project focuses on the process by which adversaries learn from each other in complex adaptive systems and tailor their activities to achieve their organizational goals in light of their opponents‟ actions. Ultimately, we will develop a meso-level model of militant networks that combines insights from political science, organizational theory, psychology, network science, and computational modeling.

Keywords: terrorism, Al-Muhajiroun, competitive adaptation, learning