A Groebner bases-based approach to backward reasoning in rule based expert systems

被引：7

作者：

Roanes-Lozano, Eugenio ^{[1
]}

Hernando, Antonio ^{[2
]}

Laita, Luis M. ^{[3
]}

Roanes-Macias, Eugenio ^{[1
]}

机构：

[1] Univ Complutense Madrid, Fac Educ, Depto Algebra, E-28040 Madrid, Spain

[2] Univ Politecn Madrid, Escuela Univ Informat, Depto Sistemas Inteligentes Aplicados, Madrid 28031, Spain

[3] Univ Politecn Madrid, Fac Informat, Depto Inteligencia Artificial, E-28660 Madrid, Spain

来源：

ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE | 2009年 / 56卷 / 3-4期

关键词：

Rule based expert systems; Logic and symbolic computing; Groebner bases; Discovery; GROBNER BASES; LOGIC; ALGORITHM; DIAGNOSIS; ALGEBRA;

D O I：

10.1007/s10472-009-9147-4

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this paper is to present theoretically a new algebraic method for detecting potentially dangerous states in a Rule Based Expert System whose knowledge is represented by propositional Boolean logic. Given a dangerous state which does not happen at present, our method is able to detect a possible input fact such that, if it also occurred, the dangerous situation really would happen. This method, inspired by automatic discovery of geometric theorems, is based on calculating just one reduced Groebner basis of a polynomial ideal representing the system's knowledge. An implementation in the computer algebra system Maple is included.

引用

页码：297 / 311

页数：15

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