Conditional Syntax Splitting for Non-monotonic Inference Operators

被引:0
|
作者
Heyninck, Jesse [1 ]
Kern-Isberner, Gabriele [2 ]
Meyer, Thomas [3 ,4 ]
Haldimann, Jonas Philipp [5 ]
Beierle, Christoph [5 ]
机构
[1] Open Univ, Heerlen, Netherlands
[2] Tech Univ Dortmund, Dortmund, Germany
[3] Univ Cape Town, Rondebosch, South Africa
[4] CAIR, Rondebosch, South Africa
[5] FernUniv, Hagen, Germany
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D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Syntax splitting is a property of inductive inference operators that ensures we can restrict our attention to parts of the conditional belief base that share atoms with a given query. To apply syntax splitting, a conditional belief base needs to consist of syntactically disjoint conditionals. This requirement is often too strong in practice, as conditionals might share atoms. In this paper we introduce the concept of conditional syntax splitting, inspired by the notion of conditional independence as known from probability theory. We show that lexicographic inference and system W satisfy conditional syntax splitting, and connect conditional syntax splitting to several known properties from the literature on non-monotonic reasoning, including the drowning effect.
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页码:6416 / 6424
页数:9
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