摘要
一、引言当今专家系统已逐步成为人工智能中影响最大、应用最广泛的领域之一。然而,尽管专家系统技术在具有良结构的狭窄领域内表现出很高的性能,但仍存在许多问题。如:·处理困难或不常见问题时性能急剧下降;·由于系统知识库的非结构化,系统知识难以维护和修改;·系统不能积累以往问题求解的经验;·系统行为的解释仅仅是启发式推理规则的再现,缺乏理论支持,不能令人信服。之所以存在上述问题。
It is clear that expert system's technology is one of AI's greatest successes so far.Currently we see an ever increasing application of expert systems.Yet there are also a number of well-recognized problems associated with the new technology. To alleviate the limitations of the current generation expert systems,the key is to develop the deep knowledge of the problem domain.This paper proposes an ap- proach to the object-oriented causal reasoning about the implication of causal event stream,in arbitrarily complex causal network.The aim of our work is to develop an environment for capturing the deep knowledge in a special application domain and to support deep reasoning.This system has been prototyped in an object-oriented extension to Prolog.The impact that these two paradigms,logic and objects,have had on the design is discussed.Several example applications have also been presented to illustrate the extensibility of the environment.
出处
《计算机科学》
CSCD
北大核心
1991年第5期43-49,共7页
Computer Science
基金
国家高技术发展计划资助课题
