{"id":{"repo_id":"nps","oai_identifier":"oai:calhoun.nps.edu:10945/66137"},"canonical_url":"https://search.dev.ndltd.org/etd/nps/oai:calhoun.nps.edu:10945/66137","repository":{"repo_id":"nps","name":"Naval Postgraduate School","base_url":"https://calhoun.nps.edu/server/oai/request"},"display":{"title":"TOURNAMENT-WINNING STRATEGY FOR ITERATED OPTIONAL PRISONER'S DILEMMA","abstract":"Iterated optional prisoner's dilemma (IOPD) is an adversarial game that can be used to model several real-world scenarios, from mutual grooming between primates to alliances between business firms. This study utilizes simulation techniques to determine winning strategies for IOPD tournaments in a variety of initial conditions. Machine learning techniques are used to iteratively improve upon the winning strategy, culminating in a single undefeated strategy. The outcome of this study is a single strategy that we claim is likely to win an IOPD tournament for most reasonable initial conditions.","abstract_html":"Iterated optional prisoner's dilemma (IOPD) is an adversarial game that can be used to model several real-world scenarios, from mutual grooming between primates to alliances between business firms. This study utilizes simulation techniques to determine winning strategies for IOPD tournaments in a variety of initial conditions. Machine learning techniques are used to iteratively improve upon the winning strategy, culminating in a single undefeated strategy. The outcome of this study is a single strategy that we claim is likely to win an IOPD tournament for most reasonable initial conditions.","abstract_has_math":false,"creators":["Shamma, Ahmed A."],"institution":"Monterey, CA; Naval Postgraduate School","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Computer Science (CS)","school":null,"contributors":[],"advisors":["Kroll, Joshua A."],"committee_chairs":[],"committee_members":[],"year":2000,"date_issued":"2000-09","date_published":"2000-09","updated_at":"2026-07-27T20:24:57Z","subjects":[],"languages":[],"rights":["This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. 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Copyright protection is not available for this work in the United States"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10945/66137"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Includes supplementary material"]},{"key":"dc:description.abstract","label":"Abstract","values":["Iterated optional prisoner's dilemma (IOPD) is an adversarial game that can be used to model several real-world scenarios, from mutual grooming between primates to alliances between business firms. This study utilizes simulation techniques to determine winning strategies for IOPD tournaments in a variety of initial conditions. Machine learning techniques are used to iteratively improve upon the winning strategy, culminating in a single undefeated strategy. The outcome of this study is a single strategy that we claim is likely to win an IOPD tournament for most reasonable initial conditions."]},{"key":"dc:title","label":"Title","values":["TOURNAMENT-WINNING STRATEGY FOR ITERATED OPTIONAL PRISONER'S DILEMMA"]}]}],"canonical_facts":{"dc:contributor.advisor":["Kroll, Joshua A."],"dc:contributor.department":["Computer Science (CS)"],"dc:creator":["Shamma, Ahmed A."],"dc:date":["Sep-20"],"dc:date.accessioned":["2020-11-18T00:23:21Z"],"dc:date.available":["2020-11-18T00:23:21Z"],"dc:date.issued":["2000-09"],"dc:description":["Includes supplementary material"],"dc:description.abstract":["Iterated optional prisoner's dilemma (IOPD) is an adversarial game that can be used to model several real-world scenarios, from mutual grooming between primates to alliances between business firms. This study utilizes simulation techniques to determine winning strategies for IOPD tournaments in a variety of initial conditions. Machine learning techniques are used to iteratively improve upon the winning strategy, culminating in a single undefeated strategy. The outcome of this study is a single strategy that we claim is likely to win an IOPD tournament for most reasonable initial conditions."],"dc:identifier.uri":["https://hdl.handle.net/10945/66137"],"dc:publisher":["Monterey, CA; Naval Postgraduate School"],"dc:rights":["This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States"],"dc:title":["TOURNAMENT-WINNING STRATEGY FOR ITERATED OPTIONAL PRISONER'S DILEMMA"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T20:24:57Z"}