Nonmonotonic reasoning, preferential models and cumulative logics
Artificial Intelligence
Fundamenta Informaticae - Special issue: logics for artificial intelligence
A Logical Framework for Integrating Inconsistent Information in Multiple Databases
FoIKS '02 Proceedings of the Second International Symposium on Foundations of Information and Knowledge Systems
Non-deterministic Multiple-valued Structures
Journal of Logic and Computation
Consistent query answering in databases
ACM SIGMOD Record
Distance semantics for database repair
Annals of Mathematics and Artificial Intelligence
Distance-based paraconsistent logics
International Journal of Approximate Reasoning
Implementing semantic merging operators using binary decision diagrams
International Journal of Approximate Reasoning
Reasoning under inconsistency: A forgetting-based approach
Artificial Intelligence
Non-deterministic Multi-valued Logics--A Tutorial
ISMVL '10 Proceedings of the 2010 40th IEEE International Symposium on Multiple-Valued Logic
Similarity-based inconsistency-tolerant logics
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Studia Logica
ICDT'07 Proceedings of the 11th international conference on Database Theory
A preferential framework for trivialization-resistant reasoning with inconsistent information
JELIA'12 Proceedings of the 13th European conference on Logics in Artificial Intelligence
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Distance-based reasoning is a well-known approach for defining non-monotonic and paraconsistent formalisms, which so far has been mainly used in the context of standard two-valued semantics. In this paper, we extend this approach to arbitrary denotational semantics by considering dissimilarities, a generalization of distances. Dissimilarity-based reasoning is then applied for handling inconsistency in knowledge-based systems using various non-classical logics. This includes logics defined by multi-valued semantics, non-deterministic semantics, and possible-worlds (Kripke-style) semantics. In particular, we show that our approach allows to define a variety of inconsistency-tolerant entailment relations, and that it extends many well-studied forms of reasoning in the context of belief revision and database integration.