摘要
许多学者将因果关系这一概念应用于基于模型的诊断领域.然而,他们的研究只局限于简单因果理论.该文提出的扩展的因果理论则包容了更多的信息,指出了扩展的因果理论的诊断空间小于等于相应简单因果理论的诊断空间.另外,还将扩展的因果理论用于测试领域,证明了对于封闭的扩展的因果理论,溯因鉴别诊断等于基于一致性鉴别诊断.
Many researchers have applied the concept of causation to model based diagnosis. However, their researches are limited to simple causal theory. In this paper, the concept of generalized causal theory that contains more information is proposed. It is pointed out that the diagnostic space of a generalized causal theory is smaller than or equal to that of the corresponding simple causal theory. Furthermore, generalized causal theory is applied to the area of test. It is demonstrated that for closed generalized causal theory, the abductive differential diagnosis is equivalent to the consistency based differential diagnosis.
出处
《软件学报》
EI
CSCD
北大核心
1999年第7期719-723,共5页
Journal of Software
基金
国家自然科学基金
国家教育部博士点基金
关键词
因果理论
鉴别诊断
模型诊断
人工智能
Simple causal theory, generalized causal theory, model based diagnosis, test, differential diagnosis.