BELIEF UPDATING FROM INTEGRITY CONSTRAINTS AND QUERIES

被引:14
作者
DERAEDT, L
BRUYNOOGHE, M
机构
[1] Department of Computer Science, Katholieke Universiteit Leuven, B-3001 Heverlee
关键词
CONCEPT-LEARNING; KNOWLEDGE BASE UPDATING; INTEGRITY CONSTRAINTS; ORACLE; MACHINE LEARNING; INDUCTIVE INFERENCE; DATA BASES; KNOWLEDGE BASES; BELIEF REVISION; BELIEF UPDATING;
D O I
10.1016/0004-3702(92)90075-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
It is argued that the problems of intensional knowledge base updating and incremental concept-learning-when formulated in a logical framework-can be understood as instances of the more general problem of belief updating. This insight allows interesting cross-fertilization between both areas. To support this claim, we sketch a simple extension of Shapiro's Model Inference System that solves the belief updating problem within a restricted subset of first order logic. This extension uses integrity constraints and allows for the assertion of non-unit clauses. The former generalizes the use of examples in concept-learning whereas the latter generalizes the set of revisions considered in knowledge base updating.
引用
收藏
页码:291 / 307
页数:17
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