The Possibilistic Horn Non-Clausal Knowledge Bases
Gonzalo E. Imaz

TL;DR
This paper introduces a new class of possibilistic non-clausal knowledge bases and a resolution method, enabling efficient reasoning directly on non-clausal formulas, which improves practical applicability in uncertain and inconsistent information scenarios.
Contribution
It defines the Possibilistic Horn Non-Clausal class and a novel non-clausal resolution method, demonstrating polynomial-time computation of inconsistency degrees.
Findings
Defines Possibilistic Horn Non-Clausal Knowledge Bases.
Introduces Possibilistic Non-Clausal Unit-Resolution method.
Proves polynomial-time complexity for inconsistency degree computation.
Abstract
Posibilistic logic is the most extended approach to handle uncertain and partially inconsistent information. Regarding normal forms, advances in possibilistic reasoning are mostly focused on clausal form. Yet, the encoding of real-world problems usually results in a non-clausal (NC) formula and NC-to-clausal translators produce severe drawbacks that heavily limit the practical performance of clausal reasoning. Thus, by computing formulas in its original NC form, we propose several contributions showing that notable advances are also possible in possibilistic non-clausal reasoning. {\em Firstly,} we define the class of {\em Possibilistic Horn Non-Clausal Knowledge Bases,} or , which subsumes the classes: possibilistic Horn and propositional Horn-NC. is shown to be a kind of NC analogous of the standard Horn class. {\em…
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Taxonomy
TopicsLogic, Reasoning, and Knowledge · Advanced Algebra and Logic · Bayesian Modeling and Causal Inference
