Propositional knowledge base revision and minimal change
Artificial Intelligence
On the semantics of theory change: arbitration between old and new information
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
ACM Transactions on Database Systems (TODS)
Integration of weighted knowledge bases
Artificial Intelligence
Infobase Change: A First Approximation
Journal of Logic, Language and Information
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
Social Choice, Merging, and Elections
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Social choice theory, belief merging, and strategy-proofness
Information Fusion
A split-combination approach to merging knowledge bases in possibilistic logic
Annals of Mathematics and Artificial Intelligence
Journal of Artificial Intelligence Research
A framework for managing uncertain inputs: An axiomization of rewarding
International Journal of Approximate Reasoning
Logic-based fusion of complex epistemic states
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
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Intelligent agents are often faced with the problem of trying to merge possibly conflicting pieces of information obtained from different sources into a consistent view of the world. We propose a framework for the modelling of such merging operations with roots in the work of Spohn [14]. Unlike most approaches we focus on the merging of epistemic states, not knowledge bases. We construct a number of plausible merging operations and measure them against various properties that merging operations ought to satisfy. Finally, we discuss the connection between merging and the use of infobases [9], [10].