Introducing a method for modeling knowledge bases in expert systems using the example of large software development projects
Introducing a method for modeling knowledge bases in expert systems using the example of large software development projects
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DOI：
10.14569/ijacsa.2015.061201
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发表时间：
2015
影响因子：
0.9
通讯作者：
F. Füßl;Detlef Streitferdt;Weijiao Shang;Anne Triebel
中科院分区：
文献类型：
--
作者：
F. Füßl;Detlef Streitferdt;Weijiao Shang;Anne Triebel
本文的目标是开发一个元模型，这为开发高度可扩展的人工智能系统提供了基础，这些系统应该能够根据不同的动态和特定的影响自主决策。人工神经网络为开发多层人类可读模型建立了切入点，该模型作为知识库，可用于演绎和归纳推理的进一步研究。一个图形理论的考虑给出了一个详细的视图到模型结构。此外，它的模型介绍了使用大型软件开发项目的例子。说明了约束和演绎推理元素修剪的集成，这是高效执行演绎推理所必需的。
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.