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
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
Merging with Integrity Constraints
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
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
Logic-based approaches to information fusion
Information Fusion
On the measure of conflicts: Shapley Inconsistency Values
Artificial Intelligence
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
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Two conciliation processes for intelligent agents based on an iterated merge-then-revise change function for belief profiles are introduced and studied. The first approach is skeptical in the sense that at any revision step, each agent considers that her current beliefs are more important than the current beliefs of the group, while the other case is considered in the second, credulous approach. Some key features of such conciliation processes are pointed out for several merging operators; especially, the convergence issue, the existence of consensus and the properties of the induced iterated merging operators are investigated.