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
Combining Multiple Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Arbitration (or How to Merge Knowledge Bases)
IEEE Transactions on Knowledge and Data Engineering
A Practical Approach to Fusing Prioritized Knowledge Bases
EPIA '99 Proceedings of the 9th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
Logical Preference Representation and Combinatorial Vote
Annals of Mathematics and Artificial Intelligence
Artificial Intelligence - Special issue on nonmonotonic reasoning
Social choice theory, belief merging, and strategy-proofness
Information Fusion
Merging stratified knowledge bases under constraints
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Inconsistency management and prioritized syntax-based entailment
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Quota and Gmin merging operators
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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Current merging methods for stratified knowledge bases are often based on the commensurability assumption, i.e. all knowledge bases share a common scale. However, this assumption is too strong in practice. In this paper, we propose a family of operators to merge stratified knowledge bases without commensurability assumption. Our merging operators generalize the quota operators, a family of important merging operators in classical logic. Both logical properties and computational complexity issues of the proposed operators are studied.