An Inconsistency-Tolerant Approach to Information Merging Based on Proposition Relaxation

被引:0
作者
Schockaert, Steven [1 ]
Prade, Henri [2 ]
机构
[1] Univ Ghent, Dept Appl Math & Comp Sci, B-9000 Ghent, Belgium
[2] Univ Paul Sabatier, Toulouse Univ, IRIT, CNRS, F-31062 Toulouse 09, France
来源
PROCEEDINGS OF THE TWENTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE (AAAI-10) | 2010年
关键词
KNOWLEDGE;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Inconsistencies between different information sources may arise because of statements that are inaccurate, albeit not completely false. In such scenarios, the most natural way to restore consistency is often to interpret assertions in a more flexible way, i.e. to enlarge (or relax) their meaning. As this process inherently requires extra-logical information about the meaning of atoms, extensions of classical merging operators are needed. In this paper, we introduce syntactic merging operators, based on possibilistic logic, which employ background knowledge about the similarity of atomic propositions to appropriately relax propositional statements.
引用
收藏
页码:363 / 368
页数:6
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