Defeating terrorist networks with game theory

Tomasz P. Michalak, Talal Rahwan, Oskar Skibski, Michael Wooldridge

Research output: Contribution to journalReview article

Abstract

One key problem is that of identifying the key members of the organization using information about the terrorist network's topology: this capability would enable security agencies to focus severely limited resources on just those key members. many standard measures of centrality from the field of social network analysis can be used. Centrality measures aim to give a numerical characterization of a node's significance in a network. In contrast, according to closeness centrality, a node's importance is based on the average distance between that node and other nodes in the network. Although the standard measures indeed deliver nontrivial insights, they cannot capture certain important aspects of centrality in a terrorist organization. Unfortunately, due to their inherent combinatorial nature, computing solution concepts for coalitional games is often computationally challenging.

Original languageEnglish (US)
Article number7030270
Pages (from-to)53-61
Number of pages9
JournalIEEE Intelligent Systems
Volume30
Issue number1
DOIs
StatePublished - Jan 1 2015

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Artificial Intelligence

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    Michalak, T. P., Rahwan, T., Skibski, O., & Wooldridge, M. (2015). Defeating terrorist networks with game theory. IEEE Intelligent Systems, 30(1), 53-61. [7030270]. https://doi.org/10.1109/MIS.2015.11