13 August 2004 Mining simulation data for insights about a decision space: application to an urban combat COA
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We start with a vision of an integrated decision architecture to assist in the various stages and subtasks of decisionmaking. We briefly describe how the Seeker-Filter-Viewer (S-F-V) architecture for multi-criterial decision support helps realize many components of that vision. The rest of the paper is devoted to one of the components: developing insights about the course of action (COA) decision space from COA simulations. We start with data obtained from multiple simulation executions of an urban combat COA in a specified scenario, where the stochastic nature of different executions produce a range of intermediate events and final outcomes. The Viewer in the S-F-V decision architecture is used to make and visually test hypotheses about how sensitive different events and outcomes are to different aspects of the COA and to various intermediate events. The analyst engages in a cycle of hypothesis making, visually evaluating the hypothesis, and making further hypotheses. A set of snapshots illustrates an investigational sequence of abstractions in an example of iterating on hypotheses. The synergy of data mining tools, high performance computing, and advanced high-resolution combat simulation has the potential to assist battle planners to make better decisions for imminent combat.
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B. Chandrasekaran, B. Chandrasekaran, John R. Josephson, John R. Josephson, Janet O'May, Janet O'May, Eric Heilman, Eric Heilman, Richard C. Kaste, Richard C. Kaste, } "Mining simulation data for insights about a decision space: application to an urban combat COA", Proc. SPIE 5423, Enabling Technologies for Simulation Science VIII, (13 August 2004); doi: 10.1117/12.542602; https://doi.org/10.1117/12.542602

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