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Communication Dans Un Congrès Année : 2009

A general framework for revising belief based using qualitative Jeffrey's rule

Résumé

Intelligent agents require methods to revise their epistemic state as they acquire new information. Jeffrey’s rule, which extends conditioning to uncertain inputs, is currently used for revising probabilistic epistemic states when new information is uncertain. This paper analyses the expressive power of two possibilistic counterparts of Jeffrey’s rule for modeling belief revision in intelligent agents. We show that this rule can be used to recover most of the existing approaches proposed in knowledge base revision, such as adjustment, natural belief revision, drastic belief revision, revision of an epistemic by another epistemic state. In addition, we also show that that some recent forms of revision, namely improvement operators, can also be recovered in our framework.

Dates et versions

hal-03353606 , version 1 (24-09-2021)

Identifiants

Citer

Salem Benferhat, Didier Dubois, Henri Prade, Mary-Anne Williams. A general framework for revising belief based using qualitative Jeffrey's rule. 18th International Symposium on Methodologies for Intelligent Systems (ISMIS 2009), Sep 2009, Prague, Czech Republic. pp.612-621, ⟨10.1007/978-3-642-04125-9_64⟩. ⟨hal-03353606⟩
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