Discrete duality for 3-valued Łukasiewicz–Moisil algebras

2017 ◽  
Vol 10 (01) ◽  
pp. 1750003 ◽  
Author(s):  
Gustavo Pelaitay
Keyword(s):  
Computer Science ◽  
Unary Operation ◽  
The Other ◽  
Representation Theorems ◽  
Kleene Algebra ◽  
Other Hand ◽  
Lecture Notes ◽  
De Morgan Algebras ◽  
Relational Representation

In 2011, Düntsch and Orłowska obtained a discrete duality for regular double Stone algebras. On the other hand, it is well known that regular double Stone algebras are polinominally equivalent to [Formula: see text]-valued Łukasiewicz–Moisil algebras (or LM3-algebras). In [R. Cignoli, Injective De Morgan and Kleene algebra, Proc. Amer. Math. Soc. 47 (1975) 269–278], LM3-algebras are considered as a Kleene algebras [Formula: see text] endowed with a unary operation [Formula: see text], satisfying the properties: [Formula: see text] [Formula: see text] and [Formula: see text] Motivated by this result, in this paper, we determine another discrete duality for LM3-algebras, extending the discrete duality to De Morgan algebras described in [W. Dzik, E. Orłowska and C. van Alten, Relational representation theorems for general lattices with negations, in Relations and Kleene Algebra in Computer Science, Lecture Notes in Computer Science, Vol. 4136 (Springer, Berlin, 2006), pp. 162–176].

Discrete duality for De Morgan Algebras with operators

2019 ◽  
Vol 12 (01) ◽  
pp. 1950010 ◽  
Author(s):  
Verónica Gregori
Keyword(s):  
Computer Science ◽  
Representation Theorems ◽  
Kleene Algebra ◽  
Lecture Notes ◽  
De Morgan Algebras ◽  
Relational Systems ◽  
Relational Representation

A discrete duality is a relationship between classes of algebras and classes of relational systems (frames). In this paper, discrete dualities are presented for De Morgan algebras with various kind of unary operators. To do this, we will extend the discrete duality given in [W. Dzik, E. Orłowska and C. van Alten, Relational representation theorems for general lattices with negations, in Relations and Kleene Algebra in Computer Science, Lecture Notes in Computer Science, Vol. 4136 (Springer, Berlin, 2006), pp. 162–176], for De Morgan algebras.

Tense De Morgan S4-algebras

2021 ◽  
pp. 2250014
Author(s):  
Cecilia Segura
Keyword(s):  
Computer Science ◽  
Representation Theorems ◽  
Ieee Computer Society ◽  
Tense Operators ◽  
Multiple Valued Logic ◽  
Lecture Notes ◽  
De Morgan Algebras ◽  
Relational Representation

In [Tense operators on De Morgan algebras, Log. J. IGPL 22(2) (2014) 255–267], Figallo and Pelaitay introduced the notion of tense operators on De Morgan algebras. Also, other notions of tense operators on De Morgan algebras were given by Chajda and Paseka in [De Morgan algebras with tense operators, J. Mult.-Valued Logic Soft Comput. 1 (2017) 29–45; The Poset-based logics for the De Morgan negation and set representation of partial dynamic De Morgan algebras, J. Mult.-Valued Logic Soft Comput. 31(3) (2018) 213–237; Set representation of partial dynamic De Morgan algebras, in 2016 IEEE 46th Int. Symp. Multiple-Valued Logic (IEEE Computer Society, 2016), pp. 119–124]. In this paper, we introduce a new notion of tense operators on De Morgan algebras and define the class of tense De Morgan [Formula: see text]-algebras. The main purpose of this paper is to give a discrete duality for tense De Morgan [Formula: see text]-algebras. To do this, we will extend the discrete duality given in [W. Dzik, E. Orłowska and C. van Alten, Relational Representation Theorems for Lattices with Negations: A Survey, Lecture Notes in Computer Science (2006), pp. 245–266], for De Morgan algebras.

Abstrakcja, obiekty i cywilizacja globalna

1970 ◽  
Vol 9 (1) ◽  
pp. 203-216
Author(s):  
Robert Janusz
Keyword(s):  
Complex Systems ◽  
Computer Science ◽  
Logical Analysis ◽  
The Other ◽  
Analysis And Design ◽  
Other Hand ◽  
Exact Description

The article is about an interaction between philosophy and informatics. The discussion is based on a complex example - a country, which has an evolving domain. In contemporary computer science very complex systems are modeled. However it would be impossible to model such systems with every detail, because it would be too difficult, it would be as complex as the reality itself. Frequently complex domains don't have an exact description of their behavior: some have an inadequate description, some have a contradictory one. To model such complex domains a computer science specialist acts like a philosopher: makes classifications, explanations, etc. On the other hand there have to be some philosophical presuppositions - a conviction that a logical analysis and design will work in the domain being modeled: a postulate is introduced that logos is able to capture-in the reality. The descriptions are continuously purified from irrational influences.

scholarly journals On some dimension formula for automorphic forms of weight one I

1982 ◽  
Vol 85 ◽  
pp. 213-221 ◽  
Author(s):  
Toyokazu Hiramatsu
Keyword(s):  
Fuchsian Group ◽  
Automorphic Forms ◽  
Galois Representations ◽  
The Other ◽  
Dimension Formula ◽  
Linearly Independent ◽  
Other Hand ◽  
Algebraic Properties ◽  
Lecture Notes ◽  
Weight One

Let Γ be a fuchsian group of the first kind not containing the element . We shall denote by d0 the number of linearly independent automorphic forms of weight 1 for Γ. It would be interesting to have a certain formula for d0. But, Hejhal said in his Lecture Notes 548, it is impossible to calculate d0 using only the basic algebraic properties of Γ. On the other hand, Serre has given such a formula of d0 recently in a paper delivered at the Durham symposium ([7]). His formula is closely connected with 2-dimensional Galois representations.

scholarly journals Forward and Backward Chaining with P Systems

2014 ◽  
pp. 149-158
Author(s):  
Sergiu Ivanov ◽  
Artiom Alhazov ◽  
Vladimir Rogojin ◽  
Miguel A. Gutiérrez-Naranjo
Keyword(s):  
Computer Science ◽  
Propositional Logic ◽  
Membrane Computing ◽  
Modus Ponens ◽  
The Other ◽  
P Systems ◽  
Backward Chaining ◽  
Other Hand

One of the concepts that lie at the basis of membrane computing is the multiset rewriting rule. On the other hand, the paradigm of rules is profusely used in computer science for representing and dealing with knowledge. Therefore, establishing a “bridge” between these domains is important, for instance, by designing P systems reproducing the modus ponens-based forward and backward chaining that can be used as tools for reasoning in propositional logic. In this paper, the authors show how powerful and intuitive the formalism of membrane computing is and how it can be used to represent concepts and notions from unrelated areas.

Ideen zu einer Kritik ‚algorithmischer‘ Rationalität

2019 ◽  
Vol 67 (5) ◽  
pp. 851-873
Author(s):  
Dieter Mersch
Keyword(s):  
Computer Science ◽  
20Th Century ◽  
The Other ◽  
Critical Approach ◽  
Halting Problem ◽  
Human Thought ◽  
Other Hand ◽  
The One ◽  
Mathematical Foundations

Abstract A critique of algorithmic rationalisation offers at best some initial reasons and preliminary ideas. Critique is understood as a reflection on validity. It is limited to an “epistemological investigation” of the limits of the calculable or of what appears “knowable” in the mode of the algorithmic. The argumentation aims at the mathematical foundations of computer science and goes back to the so-called “foundational crisis of mathematics” at the beginning of the 20th century with the attempt to formalise concepts such as calculability, decidability and provability. The Gödel theorems and Turing’s halting problem prove to be essential for any critical approach to “algorithmic rationalisation”. Both, however, do not provide unambiguous results, at best they run towards what later became known as “Gödel’s disjunction”. The chosen path here, however, suggests the opposite way, insofar as, on the one hand, the topos of creativity appear constitutive for what can be regarded as cognitive “algorithmic rationalisation” and which encounters systematic difficulties in the evaluation of non-trivial results. On the other hand, the investigations lead to a comparison between the “mediality” of formally generated structures, which have to distinguish between object-and metalanguages, and the “volatile” differentiality of human thought, which calls for syntactically non-simulatable sense structures.

scholarly journals Fuzzy b-Metric Spaces

2016 ◽  
Vol 11 (2) ◽  
pp. 273 ◽  
Author(s):  
Sorin Nădăban
Keyword(s):  
Control Theory ◽  
Computer Science ◽  
Metric Space ◽  
Metric Spaces ◽  
Denotational Semantics ◽  
Decomposition Theorem ◽  
The Other ◽  
Fuzzy Metric Space ◽  
Fuzzy Metric ◽  
Other Hand

Metric spaces and their various generalizations occur frequently in computer science applications. This is the reason why, in this paper, we introduced and studied the concept of fuzzy b-metric space, generalizing, in this way, both the notion of fuzzy metric space introduced by I. Kramosil and J. Michálek and the concept of b-metric space. On the other hand, we introduced the concept of fuzzy quasi-bmetric space, extending the notion of fuzzy quasi metric space recently introduced by V. Gregori and S. Romaguera. Finally, a decomposition theorem for a fuzzy quasipseudo- b-metric into an ascending family of quasi-pseudo-b-metrics is established. The use of fuzzy b-metric spaces and fuzzy quasi-b-metric spaces in the study of denotational semantics and their applications in control theory will be an important next step.

scholarly journals Forward and Backward Chaining with P Systems

2011 ◽  
Vol 2 (2) ◽  
pp. 56-66 ◽  
Author(s):  
Sergiu Ivanov ◽  
Artiom Alhazov ◽  
Vladimir Rogojin ◽  
Miguel A. Gutiérrez-Naranjo
Keyword(s):  
Computer Science ◽  
Propositional Logic ◽  
Membrane Computing ◽  
Modus Ponens ◽  
The Other ◽  
P Systems ◽  
Backward Chaining ◽  
Other Hand

One of the concepts that lie at the basis of membrane computing is the multiset rewriting rule. On the other hand, the paradigm of rules is profusely used in computer science for representing and dealing with knowledge. Therefore, establishing a “bridge” between these domains is important, for instance, by designing P systems reproducing the modus ponens-based forward and backward chaining that can be used as tools for reasoning in propositional logic. In this paper, the authors show how powerful and intuitive the formalism of membrane computing is and how it can be used to represent concepts and notions from unrelated areas.

scholarly journals Forward and Backward Chaining with P Systems

2012 ◽  
pp. 1522-1531
Author(s):  
Sergiu Ivanov ◽  
Artiom Alhazov ◽  
Vladimir Rogojin ◽  
Miguel A. Gutiérrez-Naranjo
Keyword(s):  
Computer Science ◽  
Propositional Logic ◽  
Membrane Computing ◽  
Modus Ponens ◽  
The Other ◽  
P Systems ◽  
Backward Chaining ◽  
Other Hand

One of the concepts that lie at the basis of membrane computing is the multiset rewriting rule. On the other hand, the paradigm of rules is profusely used in computer science for representing and dealing with knowledge. Therefore, establishing a “bridge” between these domains is important, for instance, by designing P systems reproducing the modus ponens-based forward and backward chaining that can be used as tools for reasoning in propositional logic. In this paper, the authors show how powerful and intuitive the formalism of membrane computing is and how it can be used to represent concepts and notions from unrelated areas.

scholarly journals A Comparative Study of Searching and Optimization Techniques in Artificial Intelligence

2020 ◽  
pp. 72-80
Author(s):  
Antim Panghal
Keyword(s):  
Artificial Intelligence ◽  
Comparative Study ◽  
Computer Science ◽  
Optimal Solution ◽  
Search Space ◽  
Optimization Techniques ◽  
The Other ◽  
Tabular Form ◽  
Other Hand ◽  
And Mathematics

Solving a problem mean looking for a solution, which is best among others. Finding a solution to a problem in Computer Science and Artificial Intelligence is often thought as a process of search through the space of possible solutions. On the other hand in Engineering and Mathematics it is thought as a process of optimization i.e. to find a best solution or an optimal solution for a problem. These reduce search space and improve its efficiency. At each and every step of search,it select which have the least futility. In this paper ,We categorize the different AI search and optimization techniques in a tabular form on the basis of their merits and demerits to make it easy to choose a technique for a particular problem.

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