Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Propositional knowledge base revision and minimal change
Artificial Intelligence
A logical theory of nonmonotonic inference and belief change
A logical theory of nonmonotonic inference and belief change
Representing and aggregating conflicting beliefs
Journal of Artificial Intelligence Research
Revision of partially ordered information: axiomatization, semantics and iteration
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Double preference relations for generalised belief change
Artificial Intelligence
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Most belief change operators in the AGM tradition assume an underlying plausibility ordering over the possible worlds which is transitive and complete. A unifying structure for these operators, based on supplementing the plausibility ordering with a second, guiding, relation over the worlds was presented in [5]. However it is not always reasonable to assume completeness of the underlying ordering. In this paper we generalise the structure of [5] to allow incomparabilities between worlds. We axiomatise the resulting class of belief removal functions, and show that it includes an important family of removal functions based on finite prioritised belief bases.