Applications of circumscription to formalizing common-sense knowledge
Artificial Intelligence
Circumscription and implicit definability
Journal of Automated Reasoning
Making believers out of computers
Artificial Intelligence
Formalizing nonmonotonic reasoning systems
Artificial Intelligence
Nonmonotonic Logic II: Nonmonotonic Modal Theories
Journal of the ACM (JACM)
Readings in Knowledge Representation
Readings in Knowledge Representation
On Indefinite Databases and the Closed World Assumption
Proceedings of the 6th Conference on Automated Deduction
Using model theory to specify AI programs
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
A decidable first-order logic for knowledge representation
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Intended models, circumscription and commonsense reasoning
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Transforming prioritized defaults and specificity into parallel defaults
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
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We propose a theory of default reasoning satisfying a list of natural postulates. These postulates imply that knowledge bases containing defaults should be understood not as sets of formulas (rules and facts) but as collections of partially ordered theories. As a result of this shift of perspective we obtain a rather natural theory of default reasoning in which priorities in interpretation of predicates are the source of nonmonotonicity in reasoning. We also prove that our theory shares a number of desirable properties (completeness, soundness etc.) with the theory of normal defaults of R. Reiter. We limit our discussion to logical properties of the proposed system and prove some theorems about it. Modal operators or second order formulas do not appear in our formalization. Instead, we augment the usual, two-part logical structures consisting of a metalevel and an object level, with a third level- a referential level. The rderential level is a partially ordered collection of defaults; it contains a more permanent part of a knowledge base. Current situations are described on the object level. The metalevel is a place for rules that can eliminate some of the models permitted by the object level and the referential level.