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 split-combination approach to merging knowledge bases in possibilistic logic
Annals of Mathematics and Artificial Intelligence
Implementing semantic merging operators using binary decision diagrams
International Journal of Approximate Reasoning
Knowledge Base Stratification and Merging Based on Degree of Support
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Merging stratified knowledge bases under constraints
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
The strategy-proofness landscape of merging
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Merging first-order knowledge using dilation operators
FoIKS'08 Proceedings of the 5th international conference on Foundations of information and knowledge systems
The Epistemic View of Belief Merging: Can We Track the Truth?
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Quota-Based merging operators for stratified knowledge bases
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
Forgetting and knowledge update
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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In this paper, two families of merging operators are considered: quota operators and Gmin operators. Quota operators rely on a simple idea: any possible world is viewed as a model of the result of the merging when it satisfies "sufficiently many" bases from the given profile (a multi-set of bases). Different interpretations of the "sufficiently many" give rise to specific operators. Each Gmin operator is parameterized by a pseudo-distance and each of them is intended to refine the quota operators (i.e., to preserve more information). Quota and Gmin operators are evaluated and compared along four dimensions: rationality, computational complexity, strategy-proofness, and discriminating power. Those two families are shown as interesting alternatives to the formula-based merging operators (which selects some formulas in the union of the bases).