FROM SIMULATION TO INSIGHTS: EXPERIMENTS IN THE USE OF A MULTI-CRITERIAL VIEWER TO DEVELOP UNDERSTANDING OF THE COA SPACE
Richard Kaste, Eric Heilman, B. Chandrasekaran, John R. Josephson · 2003
Building on advances in modeling and simulation, the U.S. Army Research Laboratory (ARL) has developed a capability for simulating detailed Courses of Action (COAs). The Ohio State University (OSU) has developed a multi-criterial decision technology known as the SeekerFilter-Viewer. In this paper, we report on initial results of a collaborative effort between researchers at ARL and OSU in experimenting with the decision tool for mining ARL combat simulation data to gain battle-planning insights. The capability of simulating detailed COAs opens up possibilities of mining collected data for insights. Decision support systems could assist commanders in examining simulation data for relationships between COA structure and various battle objectives. The synergy of data mining tools, high performance computing, and advanced high-resolution combat simulation has potential to lead battle planners to new insights for imminent combat, translating to improved battlefield assessments and expedient modification of COAs.