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Introducing a method for modeling knowledge bases in expert systems using the example of large software development projects

机译:介绍一种以大型软件开发项目为例的专家系统中的知识库建模方法

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摘要

Goal of this paper is to develop a meta-model, which provides the basis for developing highly scalable artificial intelligence systems that should be able to make autonomously decisions based on different dynamic and specific influences. An artificial neural network builds the entry point for developing a multi-layered human readable model that serves as knowledge base and can be used for further investigations in deductive and inductive reasoning. A graph-theoretical consideration gives a detailed view into the model structure. In addition to it the model is introduced using the example of large software development projects. The integration of Constraints and Deductive Reasoning Element Pruning are illustrated, which are required for executing deductive reasoning efficiently.
机译:本文的目标是开发一个元模型,该模型为开发高度可扩展的人工智能系统提供基础,该系统应能够根据不同的动态和特定影响自主做出决策。人工神经网络为开发多层人类可读模型提供了切入点,该模型可作为知识库,并可用于演绎和归纳推理的进一步研究。图形理论的考虑提供了对模型结构的详细视图。除此以外,还以大型软件开发项目为例介绍了该模型。说明了约束和演绎推理元素修剪的集成,这是有效执行演绎推理所必需的。

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