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Stochastic Opponent Modeling Agents (SOMA): A Case Study with Hezbollah

Stochastic Opponent Modeling Agents (SOMA): A Case Study with Hezbollah. Aaron Mannes Mary Michael Amy Pate Amy Sliva V.S. Subrahmanian Jon Wilkenfeld Laboratory for Computational Cultural Dynamics & The Center for International Development and Conflict Management University of Maryland.

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Stochastic Opponent Modeling Agents (SOMA): A Case Study with Hezbollah

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  1. Stochastic Opponent Modeling Agents (SOMA): A Case Study with Hezbollah Aaron Mannes Mary Michael Amy Pate Amy Sliva V.S. Subrahmanian Jon Wilkenfeld Laboratory for Computational Cultural Dynamics & The Center for International Development and Conflict Management University of Maryland

  2. LCCD Approach: A Very Brief Overview • SOMA: a formal, logical-statistical reasoning language within which we can express knowledge about the behaviors of a group of interest, was used to compile a set of rules about Hezbollah behavior • Minorities at Risk Project (MAR)database tracks hundreds of variables about hundreds of minority ethnic groups worldwide and the organizations that represent them - including Hezbollah • Over 14,000 rules on Hezbollah’s behavior were extracted • Built the SOMA Terrorist Organization Portal to facilitate analysis and social networking between the analysts • Questions? Don’t Ask Me! • An upcoming presentation, by the LCCD Director V.S. Subrahmanian will discuss the technical features in greater depth • For more on MAR see the University of Maryland’s Center for International Development and Conflict Management - www.cidcm.umd.edu

  3. Hezbollah Background “Hezbollah may be the A team of terrorists, and maybe al-Qaeda is actually the B team.” - former Deputy Secretary of State Richard Armitage, Congressional Testimony September 2002 • Prior to 9/11 terrorist group responsible for the most deaths of Americans • One of the first groups to conduct suicide bombings, they’ve carried out terror attacks on three continents • Fought a capable conventional war against Israel in summer 2006 • Has a political party and provides social services in Lebanon • Has links to other terrorist groups, trans-national criminal networks, and Iran and Syria

  4. Hezbollah: Politics & Terrorism • Rules indicated a clear shift in Hezbollah strategy depending on its relation to the Lebanese state • During the Lebanese Civil War there were no elections and one of Hezbollah’s top strategies was kidnapping • When the Civil War ended, Hezbollah ran in Lebanese elections, reduced their level of kidnapping and began to launching rockets at Israel

  5. Hezbollah & Kidnapping • During the Lebanese Civil War Hezbollah was .71 likely to engage in kidnappings in any given year • When the level of soliciting external support was minor the likelihood of kidnapping rose to 1.0 • In years when Hezbollah was highly engaged in seeking external support likelihood was negligible. • Was Hezbollah subordinating its terrorist activities to the needs of its sponsors?

  6. Hezbollah: Voting & Violence • Isolating between heavy involvement in electoral politics (election years) and lesser involvement however - is revealing • Base likelihood of attacks on Israel was .62 • In off election years likelihood of attacks rises to .78 • But in election years the probability is negligible • Hezbollah subordinates its military goals to its local political needs in election years • With Lebanese politics deadlocked over the Presidential election, this provides a working theory as to why Hezbollah has not renewed hostilities against Israel

  7. Insights • First we see Hezbollah as an organization that makes careful and strategic calculations • Second we see how Hezbollah is pulled between competing influences - particularly their sponsors and their local political interests • Currently Hezbollah is appears caught between its patron’s needs and the pressures of Lebanese politics • Does this create an opportunity for a political strategy to counter-Hezbollah?

  8. Contact Information Aaron Mannes Dept. of Computer Science AV Williams Building University of Maryland College Park, MD 20742. amannes@umd.edu www.aaronmannes.com LAB: www.umiacs.umd.edu/research/LCCD/

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