{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/72645"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/72645","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Belief propagation analysis in two-player games for peer-influence social networks","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Bradwick, Matthew E. (Matthew Edward)"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Operations Research Center.","school":null,"contributors":[],"advisors":["Natasha Markuzon and Marta C. González."],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-22T22:21:22Z","subjects":["Operations Research Center."],"languages":["eng"],"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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/72645","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Natasha Markuzon and Marta C. 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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."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/72645"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Cataloged from student-submitted PDF version of thesis.","Includes bibliographical references (p. 152-153)."]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Belief propagation analysis in two-player games for peer-influence social networks"]}]}],"canonical_facts":{"dc:contributor.advisor":["Natasha Markuzon and Marta C. González."],"dc:contributor.department":["Massachusetts Institute of Technology. Operations Research Center."],"dc:contributor.other":["Massachusetts Institute of Technology. Operations Research Center."],"dc:creator":["Bradwick, Matthew E. (Matthew Edward)"],"dc:date.accessioned":["2012-09-11T17:32:37Z"],"dc:date.available":["2012-09-11T17:32:37Z"],"dc:date.issued":["2012"],"dc:description":["Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Cataloged from student-submitted PDF version of thesis.","Includes bibliographical references (p. 152-153)."],"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."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/72645"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Operations Research Center."],"dc:title":["Belief propagation analysis in two-player games for peer-influence social networks"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:22Z"}