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dc.contributor.advisorKennedy, Quinn
dc.contributor.advisorAlt, Jon
dc.contributor.authorCritz, John W.
dc.dateJun-15
dc.date.accessioned2015-08-05T23:05:26Z
dc.date.available2015-08-05T23:05:26Z
dc.date.issued2015-06
dc.identifier.urihttp://hdl.handle.net/10945/45832
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractThe military has realized that their most valuable and adaptable assets are its leaders. Understanding optimal decision-making will allow the military to more effectively train its leaders. The Cognitive Alignment with Performance Targeted Training Intervention Model (CAPTTIM) was developed to aid the training of optimal decision making. CAPTTIM determines when decision performance (categorized as near-optimal or suboptimal) is aligned or misaligned with cognitive state (categorized as exploration or exploitation): when someone thinks they have figured out the task (exploitation cognitive state), is their decision performance actually near optimal? Prior research categorized subjects’ cognitive states as exploration or exploitation, but the delineation of decision performance had yet been done. The primary focus of this thesis was to use pre-collected and de-identified data to (1) determine and validate a threshold that delineated near-optimal and suboptimal decision performance with the metric, regret, and (2) categorize the combination of cognitive state and decision performance into CAPTTIM on a trial-by-trial basis. A change point analysis of regret provided an effective threshold delineation of decision performance across all subjects. Visualization techniques were employed to categorize decision and cognitive state data into CAPTTIM on a trial-by-trial basis. Thus, CAPTTIM was validated as a means of understanding decision-making.en_US
dc.description.urihttp://archive.org/details/understandingopt1094545832
dc.publisherMonterey, California: Naval Postgraduate Schoolen_US
dc.rightsThis 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.en_US
dc.titleUnderstanding optimal decision-makingen_US
dc.typeThesisen_US
dc.contributor.departmentMOVES Academic Committee
dc.contributor.departmentComputer Science
dc.contributor.departmentMOVES Academic Committeeen_US
dc.contributor.departmentComputer Scienceen_US
dc.subject.authoroptimal decision-makingen_US
dc.subject.authorregreten_US
dc.subject.authorIowa gambling tasken_US
dc.subject.authorexponentially weighted moving averageen_US
dc.subject.authorchange point analysisen_US
dc.description.serviceCaptain, United States Marine Corpsen_US
etd.thesisdegree.nameMaster of Science in Modeling, Virtual Environments, and Simulation (MOVES)en_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineModeling, Virtual Environments, and Simulation (MOVES)en_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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