A principled analysis of merging operations in possibilistic logic

Authors:
Salem Benferhat;Didier Dubois;Souhila Kaci;Henri Prade
Affiliations:
Institut de Recherche en Informatique de Toulouse, C.N.R.S., Université Paul Sabatier, Toulouse Cedex, France;Institut de Recherche en Informatique de Toulouse, C.N.R.S., Université Paul Sabatier, Toulouse Cedex, France;Institut de Recherche en Informatique de Toulouse, C.N.R.S., Université Paul Sabatier, Toulouse Cedex, France;Institut de Recherche en Informatique de Toulouse, C.N.R.S., Université Paul Sabatier, Toulouse Cedex, France
Venue:
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Year:
2000

Citing 5
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Abstract

Possibilistic logic offers a qualitative framework for representing pieces of information associated with levels of uncertainty or priority. The fusion of multiple sources information is discussed in this setting. Different classes of merging operators are considered including conjunctive, disjunctive, reinforcement, adaptive and averaging operators. Then we propose to analyse these classes in terms of postulates. This is done by first extending the postulates for merging classical bases to the case where priorities are available.