PROBABILITY DENSITIES FOR MILITARY SIMULATION AI: FUNCTIONALITY AND IMPACT IN FOG OF WAR SCENARIOS

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dc.contributor.advisorDarken, Christian J.
dc.contributor.authorJung, Hyokwon
dc.contributor.departmentComputer Science (CS)
dc.contributor.secondreaderWade, Brian M.
dc.date.accessioned2024-08-19T16:33:49Z
dc.date.available2024-08-19T16:33:49Z
dc.date.issued2024-06
dc.description.abstractDespite significant technological advancements, the fog of war—uncertainty and incomplete information on the battlefield—continues to challenge military operations. Effective decision-making under such conditions remains a critical issue due to the lack of quantitative support tools. This thesis addresses this gap by incorporating military artificial intelligence (AI) into the hexagonal battlefield simulation environment known as the Atlatl platform, developed at Naval Postgraduate School. The research focuses on the development and evaluation of various AI algorithms, including scripted AIs, hierarchical and non-hierarchical, and reinforcement learning (RL) models. These models utilize probability distributions to enhance navigation and strategic planning under scenarios of the fog of war. By simulating numerous combat iterations, AI models demonstrate marked superiority in the precision and operational efficiency of locating and tracking enemy positions within the fog of war, which can aid commanders in decision-making. Furthermore, the insights gained from this research not only contribute to refining course of action (COA) decision-making in fog-of-war scenarios but also have practical applications in anti-submarine warfare (ASW) and maritime search and rescue (SAR) operations. This thesis highlights the effectiveness of employing AI with probability distributions to support decision-making.en_US
dc.description.distributionstatementDistribution Statement A. Approved for public release: Distribution is unlimited.en_US
dc.description.serviceLieutenant Commander, Republic of Korea Navyen_US
dc.identifier.curriculumcode399, Modeling, Virtual Environments & Simulation
dc.identifier.thesisid40093
dc.identifier.urihttps://hdl.handle.net/10945/73155
dc.publisherMonterey, CA; Naval Postgraduate Schoolen_US
dc.rightsCopyright is reserved by the copyright owner.en_US
dc.subject.authorreinforcement learningen_US
dc.subject.authorRLen_US
dc.subject.authorfog of waren_US
dc.subject.authorartificial intelligenceen_US
dc.subject.authorAIen_US
dc.subject.authorcomputer scienceen_US
dc.subject.authorcognitive AIen_US
dc.subject.authorAtlatlen_US
dc.subject.authorhexagon waren_US
dc.subject.authormodelingen_US
dc.subject.authorsimulationen_US
dc.subject.authorMOVESen_US
dc.subject.authorfogen_US
dc.subject.authorprobabilityen_US
dc.subject.authordensityen_US
dc.subject.authorprobability density functionen_US
dc.subject.authorPDFen_US
dc.subject.authoranti-submarine warfareen_US
dc.subject.authorASWen_US
dc.subject.authorsearch and rescueen_US
dc.subject.authorSARen_US
dc.subject.authorcourse of actionen_US
dc.subject.authorCOAen_US
dc.titlePROBABILITY DENSITIES FOR MILITARY SIMULATION AI: FUNCTIONALITY AND IMPACT IN FOG OF WAR SCENARIOSen_US
dc.typeThesisen_US
dspace.entity.typePublication
etd.thesisdegree.disciplineModeling, Virtual Environments, and Simulationen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.nameMaster of Science in Modeling, Virtual Environments, and Simulationen_US
relation.isDepartmentOfPublication67864e54-711d-4c0a-a6d4-439a011f2bd1
relation.isDepartmentOfPublication.latestForDiscovery67864e54-711d-4c0a-a6d4-439a011f2bd1
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