%0 Journal Article
%T Precedent Interpretation Based Incomplete Information Reasoning and Its Application<br>基于优先解释的不完全信息推理及其应用
%A YE Feng
%A XU Xiao-fei
%A WANG Ya-dong
%A <br>叶风
%A 徐晓飞
%A 王亚东
%J 软件学报
%D 1999
%I 
%X Approximate reasoning with the incomplete information is one of the difficulties that the knowledge engineering has faced. A precedent logic program theory with the property of nonmonotonicity is proposed in this paper. The synthesis evaluation for the interpretation of knowledge can be taken with the theory, such that the optimal selection of interpretation is made possible which becomes the best approach to the current knowledge. The theory completion in the significance of optimal selection is achieved and the requirement of completion and consistency of knowledge are avoided. To acquire the precedent logic programs in the applications, based on an inductive logic programming, learning algorithm is presented which incorporates the multiple inductive methods and has greater ability of induction. The presented theory and the algorithm have been applied in an expert system and gained satisfactory results.
%K Expert system
%K incomplete information reasoning
%K precedent interpretation
%K inductive logic programming<br>专家系统，不完全信息推理，优先解释，归纳逻辑程序设计.
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=8156BF7836389C3B&yid=B914830F5B1D1078&vid=F3090AE9B60B7ED1&iid=38B194292C032A66&sid=8ED630AD8C61FAE8&eid=F637763636425CAF&journal_id=1000-9825&journal_name=软件学报&referenced_num=1&reference_num=7