Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
What does a conditional knowledge base entail?
Artificial Intelligence
General patterns in nonmonotonic reasoning
Handbook of logic in artificial intelligence and logic programming (vol. 3)
Propositional Distances and Preference Representation
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Answer sets for consistent query answering in inconsistent databases
Theory and Practice of Logic Programming
Non-deterministic Multiple-valued Structures
Journal of Logic and Computation
Distance semantics for database repair
Annals of Mathematics and Artificial Intelligence
Commonsense reasoning by distance semantics
TARK '07 Proceedings of the 11th conference on Theoretical aspects of rationality and knowledge
Distance-based paraconsistent logics
International Journal of Approximate Reasoning
Distance-Based Non-Deterministic Semantics
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Minimal-change integrity maintenance using tuple deletions
Information and Computation
Some simplified forms of reasoning with distance-based entailments
Canadian AI'08 Proceedings of the Canadian Society for computational studies of intelligence, 21st conference on Advances in artificial intelligence
ICDT'07 Proceedings of the 11th international conference on Database Theory
Non-deterministic Distance Semantics for Handling Incomplete and Inconsistent Data
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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Non-deterministic matrices, a natural generalization of many-valued matrices, are semantic structures in which the value assigned to a complex formula may be chosen non-deterministically from a given set of options. We show that by combining Nmatrices and preferential metric-based considerations, one obtains a family of logics that are useful for reasoning with uncertainty. We investigate the basic properties of these logics and demonstrate their usefulness in handling incomplete and inconsistent information.