Handbook of logic in artificial intelligence and logic programming (vol. 3)
Possibilistic Merging and Distance-Based Fusion of Propositional Information
Annals of Mathematics and Artificial Intelligence
Weakening conflicting information for iterated revision and knowledge integration
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
Artificial Intelligence - Special issue on nonmonotonic reasoning
An argumentation framework for merging conflicting knowledge bases: the prioritized case
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A semantic approach for iterated revision in possibilistic logic
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
A model for the integration of prioritized knowledge bases through subjective belief games
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
| Hi-index | 0.00 |
This paper presents a new approach for merging prioritized knowledge bases in possibilistic logic. Our approach is semantically defined by a model-based merging operator in propositional logic and the merged result of our approach is a normal possibility distribution. We also give an algorithm to obtain the syntactical counterpart of the semantic approach. The logical properties of our approach are considered. Finally, we analyze the computational complexity of our merging approach.