A Variable Occurrence-Centric Framework for Inconsistency Handling

Authors: Yakoub Salhi

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Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we introduce a syntactic framework for analyzing and handling inconsistencies in propositional bases. Our approach focuses on examining the relationships between variable occurrences within conflicts. We propose two dual concepts: Minimal Inconsistency Relation (MIR) and Maximal Consistency Relation (MCR). ... Using MCRs, we develop a series of non-explosive inference relations. ... Additionally, we propose an unusual semantics that assigns truth values to variable occurrences instead of the variables themselves. The next theorem is mainly derived from Proposition 2.
Researcher Affiliation Academia Yakoub Salhi Univ. Artois, CNRS, CRIL, F-62300 Lens, France EMAIL
Pseudocode No The paper describes concepts and proofs in prose, without any dedicated pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any statement or link regarding the availability of source code for the described methodology. The only link provided is for an extended version of the paper on arXiv (http://arxiv.org/abs/2412.11868), which is a link to a paper, not code.
Open Datasets No The paper primarily uses small, illustrative propositional bases like K = {p q, p r, q r} and K2 = {p, p, p q} for examples and proofs, rather than large-scale, publicly available datasets for experimental evaluation.
Dataset Splits No The paper does not describe any experimental evaluations using datasets, and therefore, no training, testing, or validation dataset splits are provided.
Hardware Specification No The paper focuses on theoretical contributions and does not describe any computational experiments or specify hardware used.
Software Dependencies No The paper presents a theoretical framework and does not mention any specific software dependencies or version numbers required to replicate experimental results.
Experiment Setup No The paper focuses on theoretical concepts and does not include an experimental section or details about hyperparameters, training configurations, or other system-level settings.