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doi: 10.1093/logcom/exab064 , 10.60692/sd3b1-mj362 , 10.48550/arxiv.2103.07548 , 10.60692/kxr8j-k2d76
arXiv: 2103.07548
handle: 10261/304474
doi: 10.1093/logcom/exab064 , 10.60692/sd3b1-mj362 , 10.48550/arxiv.2103.07548 , 10.60692/kxr8j-k2d76
arXiv: 2103.07548
handle: 10261/304474
Abstract The aim of the paper is to analyze the expressive power of the square operator of Łukasiewicz logic: $\ast x=x\odot x$, where $\odot $ is the strong Łukasiewicz conjunction. In particular, we aim at understanding and characterizing those cases in which the square operator is enough to construct a finite MV-chain from a finite totally ordered set endowed with an involutive negation. The first of our main results shows that, indeed, the whole structure of MV-chain can be reconstructed from the involution and the Łukasiewicz square operator if and only if the obtained structure has only trivial subalgebras and, equivalently, if and only if the cardinality of the starting chain is of the form $n+1$ where $n$ belongs to a class of prime numbers that we fully characterize. Secondly, we axiomatize the algebraizable matrix logic whose semantics is given by the variety generated by a finite totally ordered set endowed with an involutive negation and Łukasiewicz square operator. Finally, we propose an alternative way to account for Łukasiewicz square operator on involutive Gödel chains. In this setting, we show that such an operator can be captured by a rather intuitive set of equations.
Intermediate logic, Rough Sets Theory and Applications, Social Sciences, Geometry, Set (abstract data type), Management Science and Operations Research, Operator (biology), Biochemistry, Gene, Łukasiewicz logic, Decision Sciences, Power set, Fuzzy Logic and Residuated Lattices, FOS: Mathematics, Data mining, Algebra over a field, Application of Soft Set Theory in Decision Making, Pure mathematics, Square (algebra), Substructural logic, Mathematics - Logic, Discrete mathematics, Computer science, Description logic, Programming language, Chemistry, Computational Theory and Mathematics, Computer Science, Physical Sciences, Cardinality (data modeling), Repressor, 03G10, 03G20, 06B20, Transcription factor, Logic (math.LO), Negation, Modal Logics, Mathematics
Intermediate logic, Rough Sets Theory and Applications, Social Sciences, Geometry, Set (abstract data type), Management Science and Operations Research, Operator (biology), Biochemistry, Gene, Łukasiewicz logic, Decision Sciences, Power set, Fuzzy Logic and Residuated Lattices, FOS: Mathematics, Data mining, Algebra over a field, Application of Soft Set Theory in Decision Making, Pure mathematics, Square (algebra), Substructural logic, Mathematics - Logic, Discrete mathematics, Computer science, Description logic, Programming language, Chemistry, Computational Theory and Mathematics, Computer Science, Physical Sciences, Cardinality (data modeling), Repressor, 03G10, 03G20, 06B20, Transcription factor, Logic (math.LO), Negation, Modal Logics, Mathematics
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