2015/09/29 by Stefan Borgwardt, Borgwardt, Stefan, Rafael Peñaloza +1
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Logic, Reasoning, and Knowledge #Natural Language Processing Techniques #Semantic Web and Ontologies #cs.AI #cs.LO
paper · pdf · doi:10.48550/arxiv.1509.08761
Workshop on Weighted Logics for Artificial Intelligence, 2015
arxiv created 2015/09/29 · openalex publication_date 2015/09/29 · arxiv updated 2015/09/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Fuzzy Description Logics (FDLs) are logic-based formalisms used to represent and reason with vague or imprecise knowledge. It has been recently shown that reasoning in most FDLs using truth values from the interval [0,1] becomes undecidable in the presence of a negation constructor and general concept inclusion axioms. One exception to this negative result are FDLs whose semantics is based on the infinitely valued Gödel t-norm (G). In this paper, we extend previous decidability results for G-IALC to deal also with qualified number restrictions. Our novel approach is based on a combination of the known crispification technique for finitely valued FDLs and the automata-based procedure originally developed for reasoning in G-IALC. The proposed approach combines the advantages of these two methods, while removing their respective drawbacks.