The above discussion also lays bare the difference of perspectives between the fusion of hard constraints and knowledge-base merging: the idea of Konieczny and Pino-Perez is to explain the fusion of plain epistemic states, understood as a set of plausible worlds, by the existence of underlying partial orderings or numerical plausibility degrees (obtained by distances), based on axioms that only use plausible sets attached to these orderings. In [67] the same authors use both hard (integrity) constraints and belief sets referring to plausible worlds, and try to extend both the AGM revision and knowledge-based merging. However, they do not envisage the merging of integrity constraints discussed in the previous section. The belief revision and merging literature takes an external point of view on cognitive processes under study. The underlying ordered structures are here a consequence of the merging postulates, but they do not appear explicitly in the axioms and they are not observable from the outside. On the contrary, our approach is to construct fusion rules that only rely on what is explicitly supplied by sources. In the sequel we consider the counterpart of our fusion postulates for ranked models, that can be expressed by means of total orders of possible worlds or by their encodings on a plausibility scale.
