Comparing and Weakening Possibilistic Knowledge Bases

被引：1

作者：

Bouzar-Benlabiod, Lydia ^{[1
,2
]}

Benferhat, Salem ^{[1
]}

Bouabana-Tebibel, Thouraya ^{[2
]}

机构：

[1] Univ Artois, CNRS, CRIL, Lens, France

[2] Ecole Natl Super Informat ESI, LCSI Lab, Algiers, Algeria

来源：

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2014年 / 22卷 / 02期

关键词：

Forgetting variables; possibilistic logic; possibilistic knowledge bases; specificity relation; SPECIFICITY; INFORMATION;

D O I：

10.1142/S0218488514500081

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Weighted logics are important tools for reasoning under uncertain knowledge. A weighted knowledge base is a set of weighted formulas of the form (phi(i),alpha(i)) where phi(i) is a propositional formula and alpha(i) is the certainty degree associated with phi(i). This paper addresses two issues in the possibility theory framework: i) how to compare two weighted knowledge bases with respect to their information contents ? and ii) how to syntactically define the concept of forgetting variables ? We show that comparing knowledge bases is the counterpart of the concept of the specificity relation defined between possibility distributions.

引用

页码：181 / 203

页数：23