Integration of weighted knowledge bases
Artificial Intelligence
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
Combining Knowledge Bases Consisting of First Order Theories
ISMIS '91 Proceedings of the 6th International Symposium on Methodologies for Intelligent Systems
Artificial Intelligence - Special issue on nonmonotonic reasoning
A negotiation-style framework for non-prioritised revision
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
Social contraction and belief negotiation
Information Fusion
Merging stratified knowledge bases under constraints
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
A logic-based axiomatic model of bargaining
Artificial Intelligence
Axiomatic characterization of belief merging by negotiation
Multimedia Tools and Applications
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Belief merging has been an active research field with many important applications. Many approaches for belief merging have been proposed, but these approaches only take the belief bases as inputs without the adequate attention to the role of agents, who provide the belief bases, thus the results achieved are merely ideal and difficult to apply in the multi-agent systems. In this paper, we present a merging approach based on the negotiation techniques. A new model is proposed in which agents gradually build their common belief base from the beliefs that they provide in each round of negotiation. A set of postulates is also introduced to characterize the logical properties of the merging results.