Inconsistent Knowledge Integration in a Probabilistic Model

Radim Jiroušek and Jiří Vomlel
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Radim Jiroušek: Institute of Information Theory and Automation, Department of Decision-Making Theory
Jiří Vomlel: Institute of Information Theory and Automation, Department of Decision-Making Theory

A chapter in Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, 1995, pp 263-270 from Springer

Abstract: Abstract In probabilistic models of knowledge based systems, the knowledge base is usually represented by a multidimensional probability distribution (Hájek et. al., 1992). Analogously, oligodimensional distributions (i.e. distributions of dimensionality cca 1 – 5) can be considered partial knowledge. Within this framework the knowledge integration process corresponds to constructing a multidimensional distribution with the given marginals. For this purpose the well known Iterative Proportional Fitting (IPF) procedure can be used.

Keywords: Partial Knowledge; Conservative Modification; Inconsistent System; Iterative Average; Iterative Proportional Fitting (search for similar items in EconPapers)
Date: 1995
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4899-1424-8_18

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DOI: 10.1007/978-1-4899-1424-8_18

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