Approximate inference in default logic and circumscription
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Tractable reasoning via approximation
Artificial Intelligence
Anytime approximate model reasoning
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Nonmonotonic reasoning: from complexity to algorithms
Annals of Mathematics and Artificial Intelligence
Implementing the Davis–Putnam Method
Journal of Automated Reasoning
Combining Multiple Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
A Logic for Anytime Deduction and Anytime Compilation
JELIA '98 Proceedings of the European Workshop on Logics in Artificial Intelligence
Preferred subtheories: an extended logical framework for default reasoning
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
How to infer from inconsistent beliefs without revising
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Hi-index | 0.00 |
A great deal of research has been devoted to nontrivial reasoning in inconsistent knowledge bases. Coherence-based approaches proceed by a consolidation operation which selects several consistent subsets of the knowledge base and an entailment operation which uses classical implication on these subsets in order to conclude. An important advantage of these formalisms is their flexibility: consolidation operations can take into account the priorities of declarations stored in the base, and different entailment operations can be distinguished according to the cautiousness of reasoning. However, one of the main drawbacks of these approaches is their high computational complexity. The purpose of our study is to define a logical framework which handles this difficulty by introducing the concepts of anytime consolidation and anytime entailment. The framework is semantically founded on the notion of resource which captures both the accuracy and the computational cost of anytime operations. Moreover, a stepwise procedure is included for improving approximations. Finally, both sound approximations and complete ones are covered. Based on these properties, we show that an anytime view of coherence-based reasoning is tenable.