Revising Weighted Knowledge Bases Using FH-Conditioning - Archive ouverte HAL
Communication Dans Un Congrès Année : 2023

Revising Weighted Knowledge Bases Using FH-Conditioning

Résumé

Conditioning is an important task for updating and revising uncertain information when new information, often considered reliable, is added. This paper deals with the so-called Fagin and Halpern (FH-)conditioning within the framework of possibility theory. We discuss in particular the computation of FH-conditioning when it is applied to weighted knowledge bases. We also compare FH-conditioning with the two forms of standard possibilistic conditioning (min-based conditioning and product-based conditioning).
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Dates et versions

hal-04209092 , version 1 (16-09-2023)

Identifiants

  • HAL Id : hal-04209092 , version 1

Citer

Omar Et-Targuy, Ahlame Begdouri, Salem Benferhat, Carole Delenne. Revising Weighted Knowledge Bases Using FH-Conditioning. ENIGMA 2023 - 1st Workshop on AI-driven heterogeneous data management: Completing, merging, handling inconsistencies and query-answeringis, Sep 2023, Rhodes, Greece. ⟨hal-04209092⟩
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