Plan recognition in a large-scale multi-agent tactical domain |
Posted on:2004-08-19 | Degree:Ph.D | Type:Thesis |
University:Georgia Institute of Technology | Candidate:Devaney, Mark David | Full Text:PDF |
GTID:2468390011970706 | Subject:Computer Science |
Abstract/Summary: | |
This research addresses the task of representing and recognizing events in a tactical domain from large-scale spatio-temporal data under conditions of limited observability and high noise with real-time response constraints. These assumptions differ from those traditionally made in plan recognition and produce a problem that combines aspects of plan recognition, pattern recognition and object tracking. This research provides evidence that parsimonious qualitative representations used to represent pair-wise interactions among agents can be combined to identify large-scale group behaviors that form the basis of increasingly complex patterns of activity. A comprehensive software application was constructed to demonstrate the claims of the thesis by evaluating performance on a real-world problem involving the recognition of a tactical maneuver in actual US Army training battles. Evaluations were conducted and performance evaluated by both novices and active military subject matter experts. |
Keywords/Search Tags: | Plan recognition, Large-scale, Tactical |
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