{"621547":{"#nid":"621547","#data":{"type":"event","title":"MS Defense by Chris Monroe","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EName:\u003C\/strong\u003E Chris Monroe\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EMaster\u0026rsquo;s Thesis Defense Meeting\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Cstrong\u003EDate:\u003C\/strong\u003E Tuesday, May 21\u003Csup\u003Est\u003C\/sup\u003E, 2019\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETime:\u003C\/strong\u003E 12:00pm\u003Cbr \/\u003E\r\n\u003Cstrong\u003ELocation: \u003C\/strong\u003EJ.S. Coon Building, room 148\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cstrong\u003EAdvisor:\u003C\/strong\u003E\u003Cbr \/\u003E\r\nAssociate Professor Rick Thomas, Ph.D. (Georgia Tech)\u003Cbr \/\u003E\r\n\u0026nbsp;\u003Cbr \/\u003E\r\n\u003Cstrong\u003EThesis Committee Members:\u003C\/strong\u003E\u003Cbr \/\u003E\r\nAssociate Professor Rick Thomas, Ph.D. (Georgia Tech)\u003C\/p\u003E\r\n\r\n\u003Cp\u003EAssociate Professor James Roberts, Ph.D. (Georgia Tech)\u003Cbr \/\u003E\r\nAssociate Professor Jamie Gorman, Ph.D. (Georgia Tech)\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u003C\/strong\u003E Optimizing Military Planners Course of Action Decision-Making\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMilitary planners are faced with ever-increasing constraints, obstacles, and priority readjustments during the course of action (COA) development. This upward trajectory places a more demanding cognitive workload on decision makers, which only helps to further complicate their jobs. An effort to mediate workload is currently ongoing in the armed services through the development of effective systems that assist the planners in COA decision-making. I proposed an experiment that uses the Tool for Multi-Objective Planning and Asset Routing (TMPLAR) to aid decision makers through the use of route filtering (via sliders) and clustering (via scatter-gather) to support the selection of high utility routes while reducing route selection latency and associated workload. Study participants went through multiple levels of COA planning in a game-like scenario-driven computer application.\u0026nbsp; I predicted that filtering and clustering tools would enhance users to select the best route based on predetermined attribute weights that reflect commander intent. Also, this study delivered feedback on perceived workload from using TMPLAR. The overarching goal of this research was to improve our understanding of military decision making to assist military leaders in using supervisory control of an optimizer for accurate, efficient route planning.\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Optimizing Military Planners Course of Action Decision-Making"}],"uid":"27707","created_gmt":"2019-05-09 16:53:37","changed_gmt":"2019-05-09 16:53:37","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-05-21T13:00:00-04:00","event_time_end":"2019-05-21T15:00:00-04:00","event_time_end_last":"2019-05-21T15:00:00-04:00","gmt_time_start":"2019-05-21 17:00:00","gmt_time_end":"2019-05-21 19:00:00","gmt_time_end_last":"2019-05-21 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"111531","name":"ms defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}