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
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Integration of weighted knowledge bases
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The ordered weighted averaging operators: theory and applications
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Beyond min aggregation in multicriteria decision: (ordered) weighted min, discri-min, leximin
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A principled analysis of merging operations in possibilistic logic
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Iterated theory base change: a computational model
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Adaptive Merging of Prioritized Knowledge Bases
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A split-combination approach to merging knowledge bases in possibilistic logic
Annals of Mathematics and Artificial Intelligence
An argumentation framework for merging conflicting knowledge bases
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Conflict Analysis and Merging Operators Selection in Possibility Theory
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AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
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ICLP '09 Proceedings of the 25th International Conference on Logic Programming
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AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Representing and aggregating conflicting beliefs
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The strategy-proofness landscape of merging
Journal of Artificial Intelligence Research
Measuring conflict and agreement between two prioritized belief bases
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Editorial: Acquiring knowledge from inconsistent data sources through weighting
Data & Knowledge Engineering
Two-Agent Conflict Resolution with Assumption-Based Argumentation
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The Epistemic View of Belief Merging: Can We Track the Truth?
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A comparison of merging operators in possibilistic logic
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
A model for the integration of prioritized knowledge bases through subjective belief games
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
Solving conflicts in information merging by a flexible interpretation of atomic propositions
Artificial Intelligence
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
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KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Quota-Based merging operators for stratified knowledge bases
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
Multiple semi-revision in possibilistic logic
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Combining multiple knowledge bases by negotiation: a possibilistic approach
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
An argumentation framework for merging conflicting knowledge bases: the prioritized case
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Adaptive Merging of Prioritized Knowledge Bases
Fundamenta Informaticae
Merging interval-based possibilistic belief bases
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
An axiomatic model for merging stratified belief bases by negotiation
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Axiomatic characterization of belief merging by negotiation
Multimedia Tools and Applications
A Model-Theoretic Approach to Belief Change in Answer Set Programming
ACM Transactions on Computational Logic (TOCL)
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The problem of merging multiple sources information is central in many information processing areas such as databases integrating problems, multiple criteria decision making, expert opinion pooling, etc. Recently, several approaches have been proposed to merge propositional bases, or sets of (non-prioritized) goals. These approaches are in general semantically defined. Like in belief revision, they use implicit priorities, generally based on Dalal's distance, for merging the propositional bases and return a new propositional base as a result. An immediate consequence of the generation of a propositional base is the impossibility of decomposing and iterating the fusion process in a coherent way with respect to priorities since the underlying ordering is lost. This paper presents a general approach for fusing prioritized bases, both semantically and syntactically, when priorities are represented in the possibilistic logic framework. Different classes of merging operators are considered depending on whether the sources are consistent, conflicting, redundant or independent. We show that the approaches which have been recently proposed for merging propositional bases can be embedded in this setting. The result is then a prioritized base, and hence the process can be coherently decomposed and iterated. Moreover, this encoding provides a syntactic counterpart for the fusion of propositional bases.