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Qualitative reasoning in Bayesian networks

Authors: GARBOLINO, PAOLO;

Qualitative reasoning in Bayesian networks

Abstract

Some probabilistic inference rules which can be compared with the inference rules of preferential logic are given and it will be shown how they work in graphical models, allowing qualitative plausible reasoning in Bayesian networks.

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Italy, Spain
Keywords

Logic in artificial intelligence, typicality, belief revision, computational efficiency, inductive logic, contraction, preferential logic, Probability and inductive logic, :68 Computer science::68T Artificial intelligence [Classificació AMS], qualitative inference rules, expansion, Bayesian networks, Classificació AMS::68 Computer science::68T Artificial intelligence, Knowledge representation, Representació del coneixement (Teoria de la informació)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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