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A Variable Occurrence-Centric Framework for Inconsistency Handling

AAAI 2025 · Probabilistic and scientific modeling › Causal discovery · approach: Counterfactual identification and bounds · 0 citations (OpenAlex)

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Proposes a syntactic, variable-occurrence-based framework for propositional inconsistency (MIRs and MCRs with dual properties), using them to define non-explosive inference relations and an occurrence-based semantics.

Problem

Classical propositional bases become uninformative under inconsistency; existing syntactic approaches (MISes, MCSes) ignore the internal syntactic structure of formulas, missing conflicts involving specific variable occurrences.

Approach

Treat conflicts as equivalence relations on variable occurrences: minimal inconsistency relations (MIRs) capture conflicts, maximal consistency relations (MCRs) describe ways to restore consistency by renaming occurrences rather than dropping formulas; MCR-based inference relations retain all formulas and variables, and an occurrence-based semantics assigns truth values to occurrences.

Key results

Surprising findings

Limitations

Experimental setup

Baselines: MCS-based inference relations LPm (Minimally Inconsistent Logic of Paradox) Forgetting-based inconsistency measure (Besnard 2016)

Builds on: Maximal consistent subsets (Rescher and Manor inference) Minimal inconsistent subsets / minimal hitting set duality (Reiter) Forgetting-based repair (Besnard 2016) Logic of Paradox (LPm) (Priest 1991)

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