Logical representation and fusion of prioritized information based on guaranteed possibility measures: Application to the distance-based merging of classical bases

In the possibility theory framework, prioritized information can be logically expressed in different formats. The most usual way, used in standard possibilistic logic, is to associate necessity degrees with propositional formulas. This paper considers another representation and fusion of prioritized information using guaranteed possibility measures. Prioritized pieces of information are then represented by sets of weighted formulas, called Delta-knowledge bases, where weights are lower bounds of guaranteed possibility degrees of formulas. We first show that the basic notions of standard possibilistic logic have natural counterparts when dealing with Delta-knowledge bases. In particular we present the inference machinery, and provide syntactic, but semantically meaningful, merging of Delta-knowledge bases. In the second part of the paper, we show that distance-based merging propositional knowledge bases can be naturally encoded using Delta-knowledge bases. Moreover, this encoding is more efficient than the necessity-based encoding of distance-based merging operator. (C) 2003 Elsevier B.V. All rights reserved.