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A Self-adapting Heuristic for Automatically Constructing TerrainAppreciation Exercises

机译:自动构建地球互惠锻炼的自适应启发式

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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.
机译:欣赏地形是对对称和不对称的战争成功的关键。培训使士兵能够掌握这个重要技能传统上,传统上需要他们的易位到所选数量的区域,每个地区都提供了所需的地形特征,尽管具有有限的品种。结果,已经证明使用这些方法是昂贵且耗时的。为了对付这一点,新的计算机辅助培训应用程序允许用户在高保真图像生成发动机呈现出地理特定的开放和城市环境中快速生成和完全培训训练。后一种方法不仅具有成本效益,而且允许任何给定的运动及其在时间上复制或系统地变化的条件。然而,即使是这种计算机辅助应用程序也具有缺点。其中一个主要是他们通常要求所有培训练习都被主题专家造成艰苦的建造。此外,运动困难通常是主观评估,并经常忽略此后。结果,这些应用程序缺乏生长和适应每个受训者的技能水平和学习曲线的能力。在本文中,我们提出了一个启发式,自动构建识别关键地形的练习。每个练习都是在独特的迭代中创建和管理,其难度水平根据该实习生在现有迭代中的正确性的基础上定制的能力。

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