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Stochastic Opponent Modeling Agents: A Case Study with Hezbollah

  • Aaron Mannes
  • Mary Michael
  • Amy Pate
  • Amy Sliva
  • V.S. Subrahmanian
  • Jonathan Wilkenfeld

Abstract

Stochastic Opponent Modeling Agents (SOMA) have been proposed as a paradigm for reasoning about cultural groups, terror groups, and other socioeconomic- political-military organizations worldwide. In this paper, we describe a case study that shows how SOMA was used to model the behavior of the terrorist organization, Hezbollah. Our team, consisting of a mix of computer scientists, policy experts, and political scientists, were able to understand new facts about Hezbollah of which even seasoned Hezbollah experts may not have been aware. This paper briefly overviews SOMA rules, explains how more than 14,000 SOMA rules for Hezbollah were automatically derived, and then describes a few key findings about Hezbollah, enabled by this framework.

Keywords

External Support Terrorist Organization Electoral Politics Medium Inter Minor Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Aaron Mannes
    • 1
  • Mary Michael
    • 1
  • Amy Pate
    • 1
  • Amy Sliva
    • 1
  • V.S. Subrahmanian
    • 1
  • Jonathan Wilkenfeld
    • 1
  1. 1.University of MarylandCollege ParkUSA

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