Disrupting Terrorist Networks, a dynamic fitness landscape approach
Philip V. Fellman, Jonathan P. Clemens, Roxana Wright, Jonathan Vos, Post, Matthew Dadmun

TL;DR
This paper explores how disrupting terrorist networks through strategic interference can backfire, emphasizing the importance of targeting influential nodes rather than easy-to-reach elements, based on a dynamic fitness landscape model.
Contribution
It applies a dynamic fitness landscape approach to terrorist networks, revealing counter-intuitive insights about targeting strategies and emphasizing the need for fundamental rethinking of counter-terrorism efforts.
Findings
Soft targets have minimal value in disruption efforts.
Interfering with easily accessible elements may worsen organizational efficiency.
Targeting influential nodes is crucial for effective disruption.
Abstract
Over a period of approximately five years, Pankaj Ghemawat of Harvard Business School and Daniel Levinthal of the Wharton School have been working on a detailed simulation (producing approximately a million fitness landscape graphs) in order to determine optimal patterns of decision-making for corporations. In 2006, we adapted this study, combining it with our own work on terrorism to examine what would happen if we inverted Ghemawat and Levinthal's findings and sought to provide disinformation or otherwise interfere with the communications and decision processes of terrorist organizations in order to optimize poor decision making and inefficiencies in organizational coordination, command and control. The bulk of this study was then presented at the 2006 annual meeting of the North American Association for Computation in the Social and Organizational Sciences. We present here an…
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Taxonomy
TopicsEvolutionary Game Theory and Cooperation
