Database Methods in Expert Systems

近年来，基于规则和基于框架的系统成为 开发广泛知识的流行工具 密集的应用。 虽然这些工具提供 对应用程序开发人员、构建专家 系统仍然是一个很大程度上特设和非常劳动密集型 活动知识表示和 演绎数据库研究使尝试 系统逻辑为基础的专家系统的方法。拟议 争论的焦点是，专家系统编程可以做得更多， 声明性的，让开发人员摆脱了 详细说明了控制策略的大部分细节。这一负担应 由系统接管，该系统将使用各种优化 技术，以达到理想的响应时间。 在本研究中，一种集规则和框架于一体的语言， 在一个屋檐下，适合不确定性推理 将被设计和实施。 纯粹是陈述性的， 这种语言将允许缩短开发阶段， 知识密集型应用程序，并使其更加可靠 并且可扩展。 工业专家系统开发人员以及 知识工程研究人员将从中受益 of this research研究.

In recent years rule-based and frame-based systems became popular tools for developing a wide range of knowledge intensive applications. Although these tools provide significant help to the application developer, building expert systems remains a largely ad hoc and a very labor-intensive activity. Recent achievements in knowledge representation and deductive database research made time ripe for attempting a systematic logic-based approach to expert systems. The proposed contention is that expert system programming can be made more declarative by releaving the developer from the burden of specifying most details of control strategy. This burden should be taken over by the system which will use various optimization techniques to achieve desirable response time. In this research, a language which integrates rules and frames under one roof, and is suitable for reasoning with uncertainty will be designed and implemented. Being purely declarative, this language will allow shortening of the development phase of knowledge-intensive applications and make them more reliable and extensible. Industrial expert system developers as well as knowledge engineering researchers will benefit from theresults of this research.