摘要
Tableau作为自动推理的有效方法之一在许多领域中有重要的应用.该文作者在已提出的布尔剪枝方法基础上,对含广义量词(交和并)规则的简化方法进行研究,建立了一套含广义量词的一阶多值逻辑公式的简化Tableau推理方法.通过实例分析,对简化前后结果对比表明,改进后的Tableau方法,在推理效率上有很大的提高.
As one of effective automated reasoning methods, Tableau has been apply to many important fields. Tableau methods with generalized quantifiers are very difficulty for computer to implement. Because the number of the branches extended is very large, a Boolean pruning method was proposed in many-valued logic. Tableau rules with such quantifiers can been simplified by providing a link between signed formulas and upset/downset in Boolean set lattices. On the basis of the presented Boolean pruning method, authors research on simplifying Tableau reasoning method for generalized meet and join to build a set of reasoning methods with generalized quantifiers in first-order many-valued logic. Through the analyses of examples and compare its performance to former approach, the result shows the improved Tableau method can have a great enhancement of the inference efficiency.
出处
《计算机学报》
EI
CSCD
北大核心
2005年第9期1514-1518,共5页
Chinese Journal of Computers
基金
国家自然科学基金(60273080
60473003)资助
作者简介
刘全，男，1969年生，博士，副教授，研究方向为智能信息处理、自动推理、地理信息系统．E-mail：quanliu@suda．edu．cn．
孙吉贵，男，1963年生，博士，教授，博士生导师，研究方向为人工智能、自动推理、行末推理．
崔志明，男，1961年生，教授，博士生导师，研究方向为知识工程、智能信息处理．
