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dc.contributor.advisorYıldız, Yıldıray
dc.contributor.authorMusavi, Neginsadat
dc.date.accessioned2017-08-03T14:08:29Z
dc.date.available2017-08-03T14:08:29Z
dc.date.copyright2017-07
dc.date.issued2017-08
dc.date.submitted2017-08-02
dc.identifier.urihttp://hdl.handle.net/11693/33526
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Mechanical Engineering, İhsan Doğramacı Bilkent University, 2018.en_US
dc.descriptionIncludes bibliographical references (leaves 61-65).en_US
dc.description.abstractPredicting the outcomes of integrating Unmanned Aerial Systems (UAS) into the National Aerospace (NAS) is a complex problem which is required to be addressed by simulation studies before allowing the routine access of UAS into the NAS. This thesis focuses on providing 2D and 3D simulation frameworks using a game theoretical methodology to evaluate integration concepts in scenarios where manned and unmanned air vehicles co-exist. The fundamental gap in the literature is that the models of interaction between manned and unmanned vehicles are insu cient: a) they assume that pilot behavior is known a priori and b) they disregard decision making processes. The contribution of this work is to propose a modeling framework, in which, human pilot reactions are modeled using reinforcement learning and a game theoretical concept called level-k reasoning to ll this gap. The level-k reasoning concept is based on the assumption that humans have various levels of decision making. Reinforcement learning is a mathematical learning method that is rooted in human learning. In this work, a classical and an approximate reinforcement learning (Neural Fitted Q Iteration) methods are used to model time-extended decisions of pilots with 2D and 3D maneuvers. An analysis of UAS integration is conducted using example scenarios in the presence of manned aircraft and fully autonomous UAS equipped with sense and avoid algorithms.en_US
dc.description.statementofresponsibilityby Neginsadat Musavi.en_US
dc.format.extentx, 65 leaves : charts (some color) ; 29 cmen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectUAS Integrationen_US
dc.subjectGame theoryen_US
dc.subjectReinforcement learningen_US
dc.titleA game theoretical framework for the evaluation of unmanned aircraft systems airspace integration conceptsen_US
dc.title.alternativeİnsansız hava araçların entegrasyon konseptlerinin değerlendirilmesi için bir oyun teori çerçevesien_US
dc.typeThesisen_US
dc.departmentDepartment of Mechanical Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB156072


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