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.