FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2017682709> ?p ?o ?g. }

• W2017682709 abstract "Fuzzy Predicate Logic with evaluated syntax together with resolution principle is presented. The paper focuses mainly on modelling and treating redudancy in knowledge bases. It presents original resolution rule together with algorithm DCF Detection of Consequent Formulas developed especially for fuzzy logic with evaluated syntax. REASONING IN FUZZY PREDICATE LOGIC WITH EVALUATED SYNTAX The problem of effective modelling and reasoning on knowledge bases rises especially when dealing with many-valued logics. We would like to recall previously devised notions and methods of fuzzy resolution principle and then show original efficient methods making such a reasoning tractable. Fuzzy Predicate Logic with Evaluated Syntax (FPL) [Novak, V., Perfilieva, I., Mockoř, J., 1999] is a well-studied and wide-used logic capable of expressing vagueness. It has a lot of applications based on robust theoretical background. It also requires an efficient formal proof theory. However the most widely applied resolution principle [Dukic, N., Avdagic, Z., 2005] brings syntactically several obstacles mainly arising from normal form transformation. There are also recent attempts of similarity based resolution [Mondal, B., Raha, S., 2012], but our approach is based on classical proof theory of FPL. FPL is associating with even harder problems when trying to use the resolution principle. Solutions to these obstacles based on the nonclausal resolution [Bachmair, L., Ganzinger, H., 1997] were already proposed in [Habiballa, H., 2006]. In this article it would be presented a natural integration of these two formal logical systems into fully functioning inference system with effective proof search strategies. It leads to the refutational resolution theorem prover for FPL (RRTPFPL). Another issue addressed in the paper concerns to the efficiency of presented inference strategies developed originally for the proving system. It is showed their perspectives in combination with standard proof-search strategies. The main problem for the fuzzy logic theorem proving lies in the large amount of possible proofs with different degrees and there is presented an algorithm (Detection of Consequent Formulas DCF) solving this problem. The algorithm is based on detection of such redundant formulas (proofs) with different degrees. The article presents the method which is the main point of the work on any automated prover. There is a lot of strategies which make proofs more efficient when we use refutational proving. We consider wellknown strategies orderings, filtration strategy, set of support etc. One of the most effective strategies is the elimination of consequent formulas. It means the check if a resolvent is not a logical consequence of a formula in set of axioms or a previous resolvent. If such a condition holds it is reasonable to not include the resolvent into the set of resolvents, because if the refutation can be deduced from it, then so it can be deduced from the original resolvent, which it implies of. Resolution and Fuzzy Predicate Logic The fuzzy predicate logic with evaluated syntax is a flexible and fully complete formalism, which will be used for the below presented extension [Novak, V., Perfilieva, I., Mockoř, J., 1999]. In order to use an efficient form of the resolution principle we have to extend the standard notion of a proof (provability value and degree) with the notion of refutational proof (refutation degree). Propositonal version of the fuzzy resolution principle has been already presented in [Habiballa, H., 2002]. We suppose that set of truth values is Lukasiewicz algebra. Therefore we assume standard notions of conjunction, disjunction etc. to be bound with Lukasiewicz operators. We will assume Lukasewicz algebra to be L L = 〈[0, 1],∧,∨,⊗,→, 0, 1〉 Proceedings 27th European Conference on Modelling and Simulation ©ECMS Webjorn Rekdalsbakken, Robin T. Bye, Houxiang Zhang (Editors) ISBN: 978-0-9564944-6-7 / ISBN: 978-0-9564944-7-4 (CD) where [0, 1] is the interval of reals between 0 and 1, which are the smallest and greatest elements respectively. Basic and additional operations are defined as" @default.
• W2017682709 created "2016-06-24" @default.
• W2017682709 creator A5011417359 @default.
• W2017682709 creator A5075488069 @default.
• W2017682709 creator A5087274656 @default.
• W2017682709 creator A5089446348 @default.
• W2017682709 date "2013-05-27" @default.
• W2017682709 modified "2023-09-23" @default.
• W2017682709 title "Modelling And Reasoning With Fuzzy Logic Redundant Knowledge Bases" @default.
• W2017682709 cites W1482914320 @default.
• W2017682709 cites W1494288912 @default.
• W2017682709 cites W1513576223 @default.
• W2017682709 cites W1534799807 @default.
• W2017682709 cites W1997196510 @default.
• W2017682709 cites W2033088754 @default.
• W2017682709 cites W2071318879 @default.
• W2017682709 cites W2110182592 @default.
• W2017682709 doi "https://doi.org/10.7148/2013-0361" @default.
• W2017682709 hasPublicationYear "2013" @default.
• W2017682709 type Work @default.
• W2017682709 sameAs 2017682709 @default.
• W2017682709 citedByCount "1" @default.
• W2017682709 countsByYear W20176827092016 @default.
• W2017682709 crossrefType "proceedings-article" @default.
• W2017682709 hasAuthorship W2017682709A5011417359 @default.
• W2017682709 hasAuthorship W2017682709A5075488069 @default.
• W2017682709 hasAuthorship W2017682709A5087274656 @default.
• W2017682709 hasAuthorship W2017682709A5089446348 @default.
• W2017682709 hasConcept C154945302 @default.
• W2017682709 hasConcept C41008148 @default.
• W2017682709 hasConcept C58166 @default.
• W2017682709 hasConceptScore W2017682709C154945302 @default.
• W2017682709 hasConceptScore W2017682709C41008148 @default.
• W2017682709 hasConceptScore W2017682709C58166 @default.
• W2017682709 hasLocation W20176827091 @default.
• W2017682709 hasOpenAccess W2017682709 @default.
• W2017682709 hasPrimaryLocation W20176827091 @default.
• W2017682709 hasRelatedWork W2096946506 @default.
• W2017682709 hasRelatedWork W2350741829 @default.
• W2017682709 hasRelatedWork W2358668433 @default.
• W2017682709 hasRelatedWork W2376932109 @default.
• W2017682709 hasRelatedWork W2382290278 @default.
• W2017682709 hasRelatedWork W2390279801 @default.
• W2017682709 hasRelatedWork W2738546080 @default.
• W2017682709 hasRelatedWork W2748952813 @default.
• W2017682709 hasRelatedWork W2899084033 @default.
• W2017682709 hasRelatedWork W3107474891 @default.
• W2017682709 isParatext "false" @default.
• W2017682709 isRetracted "false" @default.
• W2017682709 magId "2017682709" @default.
• W2017682709 workType "article" @default.