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Decomposing Inconsistencies: Marginal Contributions and Pooling Techniques

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Abstract

Inconsistency measures quantify the degree of conflict within a set of propositions. They can be broadly categorized into global measures, which assess the overall inconsistency of a set, and local measures, which evaluate the contribution of single formulas to the overall inconsistency. This paper investigates the relationship between these two classes of measures through the lens of marginal contributions and pooling mechanisms. We propose a systematic framework for deriving local inconsistency measures from global ones by employing notions of marginal contributions inspired by cooperative game theory, including Shapley and Banzhaf values. Conversely, we explore methods for constructing global inconsistency measures by aggregating local contributions using various pooling techniques. A key research question arises: which combinations of marginal contribution notions (maC) and pooling mechanisms (P) are compatible? Compatibility is defined such that, given a global measure I, applying (P) to the marginal contributions derived from I yields the same result as directly applying I, and vice versa. We analyze this compatibility condition and identify specific pairs of methods, (maC) and (P), that satisfy it across various inconsistency frameworks. Our findings provide a deeper understanding of the interplay between global and local inconsistency measures, providing a foundation for designing principled and interpretable inconsistency evaluation methods in logic-based systems.

Original languageEnglish
Title of host publicationProceedings of the 34th International Joint Conference on Artificial Intelligence, IJCAI 2025
EditorsJames Kwok
PublisherInternational Joint Conferences on Artificial Intelligence
Pages4687-4695
Number of pages9
ISBN (Electronic)9781956792065
DOIs
Publication statusPublished - 1 Jan 2025
Event34th Internationa Joint Conference on Artificial Intelligence, IJCAI 2025 - Montreal, Canada
Duration: 16 Aug 202522 Aug 2025

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference34th Internationa Joint Conference on Artificial Intelligence, IJCAI 2025
Country/TerritoryCanada
CityMontreal
Period16/08/2522/08/25

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