智能飞行教练机领域模型的混合知识表示

X. Geng, Shuxin Qin, Hongxing Chang, Yiping Yang
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引用次数: 6

摘要

经过近40年的发展,智能辅导系统(ITS)正在从实验室走向现实世界。然而,飞行训练似乎与ITS的主流应用有些脱节。原因之一是飞行训练领域的知识表示困难,特别是飞行机动的程序性知识表示困难。在简要回顾了智能交通系统中的知识表示之后,很明显,智能交通系统对知识表示的要求是自然和易于更新。概念知识树是表示结构知识和关系知识的理想方法。对于用于创建可重用逻辑的程序化知识表示,行为树是一种优雅且易于理解的解决方案。CKT和BT可以通过脚本相结合,从而提出了一种强大的混合知识表示方法。有了创作工具,领域专家甚至可以在没有知识工程师帮助的情况下工作。以正常起飞为例的单次飞行机动分析和飞行机动知识树的构建证明了混合方法是建立智能飞行训练器领域模型的合适方法。
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A hybrid knowledge representation for the domain model of intelligent flight trainer
After nearly 40 years of development, Intelligent Tutoring Systems (ITS) is moving from research labs into the real world. However, Flight training seems to be somewhat divorced from the mainstream of ITS' application. One reason is the difficulty in the knowledge representation of flight training domain, especially the procedural knowledge of flight maneuvers. After a brief review of knowledge representation in ITS, it is clear that the requirements of KR are naturalness and ease to update. Concept Knowledge Tree (CKT) is an ideal method to represent structural and relational knowledge. Behavior Tree is an elegant and understandable solution to procedural knowledge representation for creating reusable logic. CKT and BT can be combined through script and thus a powerful hybrid knowledge representation method was put forward. With authoring tools, a domain expert can even work without the help of knowledge engineer. The analysis of normal takeoff as an example of a single flight maneuver and the construction of flight maneuver knowledge tree proved the hybrid method an appropriate method to develop the domain model of intelligent flight trainer.
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