a- Generalized Semantic Resolution Method in Linguistic Truth- valued Propositional Logic L V ( n ε 2) P(

被引：1
|
作者：
Zhang, Jiafeng [1 ,2 ]
Xu, Yang [1 ]
He, Xingxing [1 ]
机构：
[1] Southwest Jiaotong Univ, Intelligent Control Dev Ctr, Chengdu 610031, Sichuan Provinc, Peoples R China
[2] Bijie Univ, Ctr Log Language & Cognit, Bijie 551700, Guizhou Provinc, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2014年 / 7卷 / 01期
基金：
美国国家科学基金会;
关键词：
Automated reasoning; Resolution principle; Semantic resolution method; Lattice-valued logic; Linguistic truth-valued lattice implication algebras; FUZZY-LOGIC;
D O I：
10.1080/18756891.2013.857895
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper is focused on -generalized semantic resolution automated reasoning method in linguistic truth-valued lattice-valued propositional logic. Concretely, -generalized semantic resolution for lattice-valued propositional logic (L(n)x L-2)P(X) is equivalently transformed into that for lattice-valued propositional logic LnP(X)(i {1,2...,n}). A similar conclusion is obtained between the alpha-generalized semantic resolution for linguistic truth-valued lattice-valued propositional logic LV(nx2)P(X) and that for lattice-valued propositional logic LV(n)P(X)(i {1,2,...,n}). Secondly, the generalized semantic resolution for lattice-valued propositional logic LnP(X) based on a chain-type truth-valued field is investigated and its soundness and weak completeness are given. The Presented work provides some foundations for resolution-based automated reasoning in linguistic truth-valued lattice-valued logic based on lattice implication algebra.
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页码：160 / 171
页数：12
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