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Belief propagation analysis in two-player games for peer-influence social networks

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dc.contributor.advisor Natasha Markuzon and Marta C. González. en_US
dc.contributor.author Bradwick, Matthew E. (Matthew Edward) en_US
dc.contributor.other Massachusetts Institute of Technology. Operations Research Center. en_US
dc.coverage.spatial a-af--- en_US
dc.date.accessioned 2012-09-11T17:32:37Z
dc.date.available 2012-09-11T17:32:37Z
dc.date.copyright 2012 en_US
dc.date.issued 2012 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/72645
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012. en_US
dc.description This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. en_US
dc.description Cataloged from student-submitted PDF version of thesis. en_US
dc.description Includes bibliographical references (p. 152-153). en_US
dc.description.abstract This thesis considers approaches to influencing population opinions during counterinsurgency efforts in Afghanistan. A discrete time, agent-based threshold model is developed to analyze the propagation of beliefs in the social network, whereby each agent has a belief and a threshold value, which indicts the willingness to be influenced by the peers. Agents communicate in stochastic pairwise interactions with their neighbors. A dynamic, two player game is formulated whereby each player strategically controls the placement of one stubborn agent over time in order to maximally influence the network according to one of two different payoff functions. The stubborn agents have opposite, immutable beliefs and exert significant influence in the network. We demonstrate the characteristics of strategies chosen by the players to improve their payoffs through simulation. Determining strategies for the players in large, complex networks in which each stubborn agent has multiple connections is difficult due to exponential increases in the strategy space that is searched. We implement two heuristic methods which are shown to significantly reduce the run time needed to find strategies without significantly reducing the quality of the strategies. Lastly, we introduce population-focused actions, such as economic stimulus projects, which when used by the players result in long-lasting changes in the beliefs of the agents in the network. en_US
dc.description.statementofresponsibility by Matthew E. Bradwick. en_US
dc.format.extent 153 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Operations Research Center. en_US
dc.title Belief propagation analysis in two-player games for peer-influence social networks en_US
dc.title.alternative Belief propagation analysis in 2-player games for peer-influence social networks en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Operations Research Center. en_US
dc.identifier.oclc 807215820 en_US


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