Abduction to plausible causes: An event-based model of belief update

被引：19

作者：

Boutilier, C

机构：

[1] Department of Computer Science, University of British Columbia, Vancouver

来源：

ARTIFICIAL INTELLIGENCE | 1996年 / 83卷 / 01期

关键词：

D O I：

10.1016/0004-3702(94)00097-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Katsuno and Mendelzon (KM) theory of belief update has been proposed as a reasonable model for revising beliefs about a changing world. However, the semantics of update relies on information which is not readily available. We describe an alternative semantical view of update in which observations are incorporated into a belief set by: (a) explaining the observation in terms of a set of plausible events that might have caused that observation; and (b) predicting further consequences of those explanations. We also allow the possibility of conditional explanations, We show that this picture naturally induces an update operator conforming to the KM postulates under certain assumptions. However, we argue that these assumptions are not always reasonable, and they restrict our ability to integrate update with other forms of revision when reasoning about action.

引用

页码：143 / 166

页数：24

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