15 April 2008 A self-adapting heuristic for automatically constructing terrain appreciation exercises
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Appreciating terrain is a key to success in both symmetric and asymmetric forms of warfare. Training to enable Soldiers to master this vital skill has traditionally required their translocation to a selected number of areas, each affording a desired set of topographical features, albeit with limited breadth of variety. As a result, the use of such methods has proved to be costly and time consuming. To counter this, new computer-aided training applications permit users to rapidly generate and complete training exercises in geo-specific open and urban environments rendered by high-fidelity image generation engines. The latter method is not only cost-efficient, but allows any given exercise and its conditions to be duplicated or systematically varied over time. However, even such computer-aided applications have shortcomings. One of the principal ones is that they usually require all training exercises to be painstakingly constructed by a subject matter expert. Furthermore, exercise difficulty is usually subjectively assessed and frequently ignored thereafter. As a result, such applications lack the ability to grow and adapt to the skill level and learning curve of each trainee. In this paper, we present a heuristic that automatically constructs exercises for identifying key terrain. Each exercise is created and administered in a unique iteration, with its level of difficulty tailored to the trainee's ability based on the correctness of that trainee's responses in prior iterations.
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S. Nanda, S. Nanda, C. L. Lickteig, C. L. Lickteig, P. S. Schaefer, P. S. Schaefer, } "A self-adapting heuristic for automatically constructing terrain appreciation exercises", Proc. SPIE 6961, Intelligent Computing: Theory and Applications VI, 69610G (15 April 2008); doi: 10.1117/12.780340; https://doi.org/10.1117/12.780340


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