Sep 2026· Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence· 0 citations· 32 references
TL;DR
A modular logical framework for both reasoning with and measuring inconsistency in propositional knowledge bases that captures several existing forms of inconsistency-tolerant reasoning, including entailment based on maximal satisfiable subsets and the minimally inconsistent Logic of Paradox.
Abstract
We propose a modular logical framework for both reasoning with and measuring inconsistency in propositional knowledge bases. The framework extends propositional logic with markers attached to occurrences of atoms and interpreted as pointers to worlds. This allows different occurrences of the same atom to be evaluated in different contexts unless they share a marker. We define paraconsistent entailment relations via abnormality functions that associate each model with a set of deviations from a preferred behavior. Each entailment relation is then defined with respect to models that are minimal under set inclusion. We show that suitable markings and abnormality functions capture several existing forms of inconsistency-tolerant reasoning, including entailment based on maximal satisfiable subsets and the minimally inconsistent Logic of Paradox. We also show how a range of inconsistency measures can be expressed in the same setting. Thus our framework provides a uniform basis for diverse approaches to inconsistency handling and measurement.
We present a unified framework for modeling
agents’ epistemic states and counterfactual conditionals.
The novelty of our approach lies at the
semantic level. We introduce a computationally
grounded semantics in which an agent’s doxastic
accessibility relation, needed to model the standard
notion of deductively closed...
E. Lorini, Dmitry Rozplokhas· Proceedings of the Thirty-Fi...· 0 citations
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J. Jafari, Davood Hosseini· Australasian Journal of Logi...· 0 citations
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