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Stochastic Opponent Modeling Agents: A Case Study with Hezbollah


Stochastic Opponent Modeling Agents: A Case Study with Hezbollah

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.

Publication Information

Full Citation: 

Mannes, Aaron, Mary Michael, Amy Pate, Amy Sliva, V.S. Subrahmanian, and Jonathan Wilkenfeld. 2008. "Stochastic Opponent Modeling Agents: A Case Study with Hezbollah." Social Computing, Behavioral Modeling, and Prediction (April): 37-45.  https://link.springer.com/chapter/10.1007/978-0-387-77672-9_6

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