The recent usage of technical systems in human-centric environments leads to the question, how to teach technical systems, e.g., robots, to understand, learn, and perform tasks desired by the human. Therefore, an accurate representation of knowledge is essential for the system to work as expected. This article mainly gives insight into different knowledge representation techniques and their categorization into various problem domains in artificial intelligence. Additionally, applications of presented knowledge representations are introduced in everyday robotics tasks. By means of the provided taxonomy, the search for a proper knowledge representation technique regarding a specific problem should be facilitated.

中文翻译：

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技术系统中的知识表示——分类法

最近在以人为中心的环境中使用技术系统导致了一个问题，即如何教技术系统（例如机器人）理解、学习和执行人类所需的任务。因此，准确的知识表示对于系统按预期工作至关重要。本文主要深入了解人工智能中不同的知识表示技术及其对各种问题领域的分类。此外，在日常机器人任务中引入了所呈现的知识表示的应用。通过所提供的分类法，应该促进针对特定问题寻找合适的知识表示技术。