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Artículos de revistas sobre el tema "Logic (symbolic and mathematical)"

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Publicado: 4 de junio de 2021

Última modificación: 29 de julio de 2024

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1

Shore, Richard A. "The Bulletin of Symbolic Logic." Bulletin of Symbolic Logic 1, no. 1 (March 1995): 1–3. http://dx.doi.org/10.1017/s107989860000826x.

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At the 1993 Annual meeting of the Association for Symbolic Logic, the Council of the association voted to establish a new journal to be called The Bulletin of Symbolic Logic. The intended goal of the Council was to produce a journal that would be both accessible and of interest to as wide an audience as possible, with the stated purpose of keeping the logic community abreast of important developments in all parts of our discipline. The first issue was to appear in March of 1995 and you now have it in your hands.In accordance with the Council resolution, we intend to publish primarily two types

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2

Peckhaus, Volker. "19th Century Logic Between Philosophy and Mathematics." Bulletin of Symbolic Logic 5, no. 4 (December 1999): 433–50. http://dx.doi.org/10.2307/421117.

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AbstractThe history of modern logic is usually written as the history of mathematical or, more general, symbolic logic. As such it was created by mathematicians. Not regarding its anticipations in Scholastic logic and in the rationalistic era, its continuous development began with George Boole's The Mathematical Analysis of Logic of 1847, and it became a mathematical subdiscipline in the early 20th century. This style of presentation cuts off one eminent line of development, the philosophical development of logic, although logic is evidently one of the basic disciplines of philosophy. One need

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3

Kim, S. H., and N. P. Suh. "Mathematical Foundations for Manufacturing." Journal of Engineering for Industry 109, no. 3 (August 1, 1987): 213–18. http://dx.doi.org/10.1115/1.3187121.

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For the field of manufacturing to become a science, it is necessary to develop general mathematical descriptions for the analysis and synthesis of manufacturing systems. Standard analytic models, as used extensively in the past, are ineffective for describing the general manufacturing situation due to their inability to deal with discontinuous and nonlinear phenomena. These limitations are transcended by algebraic models based on set structures. Set-theoretic and algebraic structures may be used to (1) express with precision a variety of important qualitative concepts such as hierarchies, (2)

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4

Davis, Martin. "American Logic in the 1920s." Bulletin of Symbolic Logic 1, no. 3 (September 1995): 273–78. http://dx.doi.org/10.2307/421156.

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In 1934 Alonzo Church, Kurt Gödei, S. C. Kleene, and J. B. Rosser were all to be found in Princeton, New Jersey. In 1936 Church founded The Journal of Symbolic Logic. Shortly thereafter Alan Turing arrived for a two year visit. The United States had become a world center for cutting-edge research in mathematical logic. In this brief survey1 we shall examine some of the writings of American logicians during the 1920s, a period of important beginnings and remarkable insights as well as of confused gropings.The publication of Whitehead and Russell's monumental Principia Mathematica [18] during th

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5

Sato, T., and Y. Kameya. "Parameter Learning of Logic Programs for Symbolic-Statistical Modeling." Journal of Artificial Intelligence Research 15 (December 1, 2001): 391–454. http://dx.doi.org/10.1613/jair.912.

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We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. definite clause programs containing probabilistic facts with a parameterized distribution. It extends the traditional least Herbrand model semantics in logic programming to distribution semantics, possible world semantics with a probability distribution which is unconditionally applicable to arbitrary logic programs including ones for HMMs, PCFGs and Bayesian networks. We also propose a new EM algorithm, the graphical EM algorithm, that runs for a class of parameterized logic pr

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6

Firnanda, Dwi Tri Fresti, and Indah Wahyuni. "Semiotic Mathematics Representation Ability Based on Symbolic in Solving SPLSV Problems in Class VII Students." Ta'dib 27, no. 1 (June 13, 2024): 205. http://dx.doi.org/10.31958/jt.v27i1.11562.

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Mathematical semiotic representation is the ability to analyze and express mathematical ideas or notions of a phenomenon and everyday problem situations into the form of signs, images, symbols, and symbols that represent them and provide meaning and explanation to a package of verbal sign messages. The symbolic stage is the stage where students have understood the symbols and concepts and have ideas that are strongly influenced by language and logic skills and students are able to manipulate symbols or symbols of a particular object. The purpose of this study was to determine the representatio

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7

Ashok, Dhananjay, Joseph Scott, Sebastian J. Wetzel, Maysum Panju, and Vijay Ganesh. "Logic Guided Genetic Algorithms (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 18 (May 18, 2021): 15753–54. http://dx.doi.org/10.1609/aaai.v35i18.17873.

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We present a novel Auxiliary Truth enhanced Genetic Algorithm (GA) that uses logical or mathematical constraints as a means of data augmentation as well as to compute loss (in conjunction with the traditional MSE), with the aim of increasing both data efficiency and accuracy of symbolic regression (SR) algorithms. Our method, logic-guided genetic algorithm (LGGA), takes as input a set of labelled data points and auxiliary truths (AT) (mathematical facts known a priori about the unknown function the regressor aims to learn) and outputs a specially generated and curated dataset that can be used

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8

Lobovikov, Vladimir O. "A wonderful analogy between Augustine’s definition of moral-value- functional sense of response-action and Philo’s definition of truth-functional sense of implication in logic." CIENCIA ergo sum 27, no. 3 (August 12, 2020): e94. http://dx.doi.org/10.30878/ces.v27n3a4.

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The paper is dvoted to interdisciplinary research at the intersection of symbolic logic, mathematical ethics, and philosophical theology. By comparing definitions of relevant functions, a surprising analogy is discovered between the well-known Philo’s precise definition of implication in logic (classical one) and Augustine’s precise definition of God’s morally good reaction to human actions. The moral-value-table-representation of Augustinian doctrine is compared with moral-value-table-representations of Pelagius’ and Leo Tolstoy’s views of adequate moral-response-actions.

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9

Riede, U. N., Joh Kensuke, and G. William Moore. "Symbolic logic model of cellular adaptation." Mathematical Modelling 7, no. 9-12 (1986): 1301–23. http://dx.doi.org/10.1016/0270-0255(86)90082-5.

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10

RAHEEM Tunde Rasheed and SAM-KAYODE Christianah Olajumoke (Ph. D). "The Use of Truth Table, Logical Reasoning and Logic Gate in Teaching and Learning Process." International Journal of Latest Technology in Engineering Management & Applied Science 13, no. 6 (June 28, 2024): 1–12. http://dx.doi.org/10.51583/ijltemas.2024.130601.

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The concept of truth table is based on the content to analyze in teaching and learning logical reasoning and logic gate, which is a visual representation of possible combination of input and output information of Boolean prepositions in logical reasoning and Boolean functions in logic gate plotted into a table. It adopts Boolean algebra for problem solving as a method or science of reasoning, or ability to argue and convince. In the teaching and learning processes of logic, formal and informal reasoning tasks are used in a variety of ways, including using symbols and entirely in plain language

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11

Mosser, Kurt. "The Grammatical Background of Kant's General Logic." Kantian Review 13, no. 1 (March 2008): 116–40. http://dx.doi.org/10.1017/s1369415400001114.

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In theCritique of Pure Reason, Kant conceives of general logic as a set of universal and necessary rules for the possibility of thought, or as a set of minimal necessary conditions for ascribing rationality to an agent (exemplified by the principle of non-contradiction). Such a conception, of course, contrasts with contemporary notions of formal, mathematical or symbolic logic. Yet, in so far as Kant seeks to identify those conditions that must hold for the possibility of thought in general, such conditions must holda fortiorifor any specific model of thought, including axiomatic treatments of

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12

Miguel Tomé, Sergio. "Towards a model-theoretic framework for describing the semantic aspects of cognitive processes." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 8, no. 4 (April 22, 2020): 83–96. http://dx.doi.org/10.14201/adcaij2019848396.

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Semantics is one of the most challenging aspects of cognitive architectures. Mathematical logic, or linguistics, highlights that semantics is essential to human cognition. The Cognitive Theory of True Conditions (CTTC) is a proposal to implement cognitive abilities and to describe the semantics of symbolic cognitive architectures based on model-theoretic semantics. This article focuses on the concepts supporting the mathematical formulation of the CTTC, its relationship to other proposals, and how it can be used as a framework for designing cognitive abilities in agents.

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13

Ferreirós, José. "La lógica matemática: una disciplina en busca de encuadre." THEORIA 25, no. 3 (September 27, 2010): 279–99. http://dx.doi.org/10.1387/theoria.717.

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We offer an analysis of the disciplinary transformations underwent by mathematical or symbolic logic since its emergence in the late 19th century. Examined are its origins as a hybrid of philosophy and mathematics, the maturity and institutionalisation attained under the label "logic and foundations," a second wave of institutionalisation in the Postwar period, and the institutional developments since 1975 in connection with computer science and with the study of language and informatics. Although some "internal history" is discussed, the main focus is on the emergence, consolidation and convo

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14

Scott, Joseph, Maysum Panju, and Vijay Ganesh. "LGML: Logic Guided Machine Learning (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 10 (April 3, 2020): 13909–10. http://dx.doi.org/10.1609/aaai.v34i10.7227.

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We introduce Logic Guided Machine Learning (LGML), a novel approach that symbiotically combines machine learning (ML) and logic solvers to learn mathematical functions from data. LGML consists of two phases, namely a learning-phase and a logic-phase with a corrective feedback loop, such that, the learning-phase learns symbolic expressions from input data, and the logic-phase cross verifies the consistency of the learned expression with known auxiliary truths. If inconsistent, the logic-phase feeds back "counterexamples" to the learning-phase. This process is repeated until the learned expressi

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15

Zhang, Hehua, Yu Jiang, William N. N. Hung, Xiaoyu Song, Ming Gu, and Jiaguang Sun. "Symbolic Analysis of Programmable Logic Controllers." IEEE Transactions on Computers 63, no. 10 (October 2014): 2563–75. http://dx.doi.org/10.1109/tc.2013.124.

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16

Mezhoud, Salim. "Language Mathematics and Mathematics Language, Reading from Computational Linguistics." Mathematical Linguistics 1, no. 1 (December 31, 2021): 7–24. http://dx.doi.org/10.58205/ml.v1i1.140.

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The language of mathematics is the system used by mathematicians to communicate mathematical ideas among themselves. This language consists of a substrate of some natural language using technical terms and grammatical conventions that are peculiar to mathematical discourse, supplemented by a highly specialized symbolic notation for mathematical formulas. mathematical characterizations of various notions of linguistic complexity include also computational linguistics, philosophical logic, knowledge representation as a branch of artificial intelligence, theoretical computer science, and co

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17

Amendola, Giovanni. "Special Issue on Logic-Based Artificial Intelligence." Algorithms 16, no. 2 (February 13, 2023): 106. http://dx.doi.org/10.3390/a16020106.

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Since its inception, research in the field of Artificial Intelligence (AI) has had a fundamentally logical approach; therefore, discussions have taken place to establish a way of distinguishing symbolic AI from sub-symbolic AI, basing the approach instead on the statistical approaches typical of machine learning, deep learning or Bayesian networks [...]

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18

Hellman, Geoffrey. "Stewart Shapiro. Second-order languages and mathematical practice. The journal of symbolic logic, vol. 50 (1985), pp. 714–742." Journal of Symbolic Logic 54, no. 1 (March 1989): 291–93. http://dx.doi.org/10.2307/2275038.

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19

Zach, Richard. "Completeness Before Post: Bernays, Hilbert, and the Development of Propositional Logic." Bulletin of Symbolic Logic 5, no. 3 (September 1999): 331–66. http://dx.doi.org/10.2307/421184.

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AbstractSome of the most important developments of symbolic logic took place in the 1920s. Foremost among them are the distinction between syntax and semantics and the formulation of questions of completeness and decidability of logical systems. David Hilbert and his students played a very important part in these developments. Their contributions can be traced to unpublished lecture notes and other manuscripts by Hilbert and Bernays dating to the period 1917–1923. The aim of this paper is to describe these results, focussing primarily on propositional logic, and to put them in their historical

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20

Patel, Usha, Parita Rajiv Oza, Riya Revdiwala, Utsav Mukeshchandra Haveliwala, Smita Agrawal, and Preeti Kathiria. "Fuzzy Logic Inference-Based Automated Water Irrigation System." International Journal of Ambient Computing and Intelligence 13, no. 1 (January 1, 2022): 1–15. http://dx.doi.org/10.4018/ijaci.304726.

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To fulfill the food interest of consistently expanding populace of our planet, it is important to do essential in the field of agribusiness. Traditional techniques for water systems like trench, wells, and precipitation are tedious and occasional. With the help of an automated water irrigation system the water, energy, and time can be moderated. This paper presents fuzzy rule logic inference-based automated water system framework. The soil moisture, weather forecast, crop status, and water-tank level are taken as input parameters. Soil moisture and water tank level can be recorded by utilizing

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21

Roberts, Alexander. "Relative Necessity and Propositional Quantification." Journal of Philosophical Logic 49, no. 4 (December 28, 2019): 703–26. http://dx.doi.org/10.1007/s10992-019-09534-8.

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AbstractFollowing Smiley’s (The Journal of Symbolic Logic, 28, 113–134 1963) influential proposal, it has become standard practice to characterise notions of relative necessity in terms of simple strict conditionals. However, Humberstone (Reports on Mathematical Logic, 13, 33–42 1981) and others have highlighted various flaws with Smiley’s now standard account of relative necessity. In their recent article, Hale and Leech (Journal of Philosophical Logic, 46, 1–26 2017) propose a novel account of relative necessity designed to overcome the problems facing the standard account. Nevertheless, the

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22

Demidov, Valery Anatolyevich. "Corrigendum to: V. A. Sokolov, “On the Existence Problem of Finite Bases of Identities in the Algebras of Recursive Functions”, Modeling and analysis of information systems, vol. 27, no. 3, pp. 304-315, 2020. DOI: https://doi.org/10.18255/1818-1015-2020-3-304-315." Modeling and Analysis of Information Systems 27, no. 4 (December 20, 2020): 510–11. http://dx.doi.org/10.18255/1818-1015-2020-4-510-511.

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The author regrets that in the original list the references [3] and [4] are in the wrong places and they should be rearranged. In addition, [3] has the wrong article title. The corrected reference list is shown below.The author would like to apologize for an inconvenience caused.References[1] A. I. Mal'tsev, “Constructive algebras I”, Russian Mathematical Surveys, vol. 16, no. 3, pp. 77-129, 1961.[2] A. I. Mal'tsev, Algoritmy i rekursivnye funktsii. Moscow: Nauka, 1965, In Russian.[3] R. M. Robinson, “Primitive recursive functions”, Bulletin of the American Mathematical Society, vol. 53, no. 1

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23

Nadweh, Rama Asad. "On The Fusion of Neural Networks and Fuzzy Logic, Membership Functions and Weights." Galoitica: Journal of Mathematical Structures and Applications 7, no. 1 (2023): 18–25. http://dx.doi.org/10.54216/gjmsa.070102.

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Fuzzy logic plays a huge role in the symbolic inference and causality associated with modern cognitive human systems. In this paper, we present a mathematical method that defines the mechanism of forming a hybrid structure in which neural networks and expert systems are connected so that one forms a primary processing stage for the other, where the neural network can act as a primary processor that processes low-level information, or as an internal Subsystem for learning tasks or generalization and classification. Where neural networks can be used to generate rules using training data and then

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24

Kim, Steven H., and Nam P. Suh. "Application of symbolic logic to the design axioms." Robotics and Computer-Integrated Manufacturing 2, no. 1 (January 1985): 55–64. http://dx.doi.org/10.1016/0736-5845(85)90008-0.

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25

Harrod, James B. "A post-structuralist revised Weil–Lévi-Strauss transformation formula for conceptual value-fields." Sign Systems Studies 46, no. 2/3 (November 19, 2018): 255–81. http://dx.doi.org/10.12697/sss.2018.46.2-3.03.

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The structuralist André-Weil–Claude-Lévi-Strauss transformation formula (CF), initially applied to kinship systems, mythology, ritual, artistic design and architecture, was rightfully criticized for its rationalism and tendency to reduce complex transformations to analogical structures. I present a revised non-mathematical revision of the CF, a general transformation formula (rCF) applicable to networks of complementary semantic binaries in conceptual value-fields of culture, including comparative religion and mythology, ritual, art, literature and philosophy. The rCF is a rule-guided formula

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26

Parisi, Luciana. "Interactive Computation and Artificial Epistemologies." Theory, Culture & Society 38, no. 7-8 (October 19, 2021): 33–53. http://dx.doi.org/10.1177/02632764211048548.

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What is algorithmic thought? It is not possible to address this question without first reflecting on how the Universal Turing Machine transformed symbolic logic and brought to a halt the universality of mathematical formalism and the biocentric speciation of thought. The article draws on Sylvia Wynter’s discussion of the sociogenic principle to argue that both neurocognitive and formal models of automated cognition constitute the epistemological explanations of the origin of the human and of human sapience. Wynter’s argument will be related to Gilbert Simondon’s reflections on ‘technical menta

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27

d'Avila Garcez, Artur, Dov M. Gabbay, Steffen Hölldobler, and John G. Taylor. "Journal of Applied Logic Special Volume on Neural-Symbolic Systems." Journal of Applied Logic 2, no. 3 (September 2004): 241–43. http://dx.doi.org/10.1016/j.jal.2004.03.001.

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28

de Mol, Liesbeth. "Closing the Circle: An Analysis of Emil Post's Early Work." Bulletin of Symbolic Logic 12, no. 2 (June 2006): 267–89. http://dx.doi.org/10.2178/bsl/1146620062.

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AbstractIn 1931 Kurt Gödel published his incompleteness results, and some years later Church and Turing showed that the decision problem for certain systems of symbolic logic has a negative solution. However, already in 1921 the young logician Emil Post worked on similar problems which resulted in what he called an “anticipation” of these results. For several reasons though he did not submit these results to a journal until 1941. This failure ‘to be the first’, did not discourage him: his contributions to mathematical logic and its foundations should not be underestimated. It is the purpose of

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29

Monk, J. Donald. "Joseph R. Shoenfield. Mathematical logic. Republication of JSL XL 234. Association for Symbolic Logic, Urbana, and A K Peters, Natick, Mass., 2001, viii + 344 pp." Bulletin of Symbolic Logic 7, no. 3 (September 2001): 376. http://dx.doi.org/10.2307/2687755.

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30

Filgueira Arias, Cándida, and Maria del Carmen Escribano Ródenas. "Mathematical Narrations and Poetry. A Mathematical Resilience Tool." Multidisciplinary Journal of School Education 11, no. 2 (22) (December 28, 2022): 357–81. http://dx.doi.org/10.35765/mjse.2022.1122.18.

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Mathematics frequently appear in stories, poetry, stories, literary narratives, in general in different literary genres. Numbers and Mathematics usually appear in the stories, poems and narratives of children's and youth literature. Likewise, in these literary genres spatial relationships, shapes, sizes, quantities, numbers are verified, and it is that in Mathematics the pillars of logic and creativity underlie (Cervera, 1983). Thus, it is intended to develop an analysis and reflection through a bibliographic review of children's and youth literature related to Mathematics as a res

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31

Cooper, Mark S., and Adam S. Przebinda. "Synaptic Conversion of Chloride-Dependent Synapses in Spinal Nociceptive Circuits: Roles in Neuropathic Pain." Pain Research and Treatment 2011 (May 30, 2011): 1–12. http://dx.doi.org/10.1155/2011/738645.

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Electrophysiological conversion of chloride-dependent synapses from inhibitory to excitatory function, as a result of aberrant neuronal chloride homeostasis, is a known mechanism for the genesis of neuropathic pain. This paper examines theoretically how this type of synaptic conversion can disrupt circuit logic in spinal nociceptive circuits. First, a mathematical scaling factor is developed to represent local aberration in chloride electrochemical driving potential. Using this mathematical scaling factor, electrophysiological symbols are developed to represent the magnitude of synaptic conver

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32

Mewada, Shivlal. "Perspectives of Fuzzy Logic and Their Applications." International Journal of Data Analytics 2, no. 1 (January 2021): 99–145. http://dx.doi.org/10.4018/ijda.2021010105.

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Fuzzy logic is a highly suitable and applicable basis for developing knowledge-based systems in engineering and applied sciences. The concepts of a fuzzy number plays a fundamental role in formulating quantitative fuzzy variable. These are variable whose states are fuzzy numbers. When in addition, the fuzzy numbers represent linguistic concepts, such as very small, small, medium, and so on, as interpreted in a particular contest, the resulting constructs are usually called linguistic variables. Each linguistic variable the states of which are expressed by linguistic terms interpreted as specif

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33

Ott, Natalie, Roland Brünken, Markus Vogel, and Sarah Malone. "Multiple symbolic representations: The combination of formula and text supports problem solving in the mathematical field of propositional logic." Learning and Instruction 58 (December 2018): 88–105. http://dx.doi.org/10.1016/j.learninstruc.2018.04.010.

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34

Simpson, Stephen G. "Partial realizations of Hilbert's program." Journal of Symbolic Logic 53, no. 2 (June 1988): 349–63. http://dx.doi.org/10.1017/s0022481200028309.

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§0. Introduction. What follows is a write-up of my contribution to the symposium “Hilbert's Program Sixty Years Later” which was sponsored jointly by the American Philosophical Association and the Association for Symbolic Logic. The symposium was held on December 29,1985 in Washington, D. C. The panelists were Solomon Feferman, Dag Prawitz and myself. The moderator was Wilfried Sieg. The research which I discuss here was partially supported by NSF Grant DMS-8317874.I am grateful to the organizers of this timely symposium on an important topic. As a mathematician I particularly value the opport

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35

Chernoskutov, Yu Yu. "On the Syllogistic of G. Boole." Discourse 7, no. 2 (April 29, 2021): 5–15. http://dx.doi.org/10.32603/2412-8562-2021-7-2-5-15.

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Introduction. This article focuses on the investigation of Boole’s theory of categorical syllogism, exposed in his book “The Mathematical analysis of Logic”. That part of Boolean legacy has been neglected in the prevailed investigations on the history of logic; the latter provides the novelty of the work presented.Methodology and sources. The formal reconstruction of the methods of algebraic presentation of categorical syllogism, as it is exposed in the original work of Boole, is conducted. The character of Boolean methods is investigated in the interconnections with the principles of symbolic

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36

Kilmister, C. W. "Mathematical logic, by J. R. Shoenfield. Pp. 344. £24. 2001. ISBN 1 56881 135 7 (Association for Symbolic Logic, in collaboration with A. K. Peters Ltd.)." Mathematical Gazette 87, no. 509 (July 2003): 407. http://dx.doi.org/10.1017/s0025557200173474.

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37

WHITEN, BILL. "A SIMPLE ALGORITHM FOR DEDUCTION." ANZIAM Journal 51, no. 1 (July 2009): 102–22. http://dx.doi.org/10.1017/s1446181109000352.

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AbstractIt is shown that a simple deduction engine can be developed for a propositional logic that follows the normal rules of classical logic in symbolic form, but the description of what is known about a proposition uses two numeric state variables that conveniently describe unknown and inconsistent, as well as true and false. Partly true and partly false can be included in deductions. The multi-valued logic is easily understood as the state variables relate directly to true and false. The deduction engine provides a convenient standard method for handling multiple or complicated logical rel

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38

BEGGS, EDWIN, JOSÉ FÉLIX COSTA, DIOGO POÇAS, and JOHN V. TUCKER. "Computations with oracles that measure vanishing quantities." Mathematical Structures in Computer Science 27, no. 8 (June 23, 2016): 1315–63. http://dx.doi.org/10.1017/s0960129516000219.

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We consider computation with real numbers that arise through a process of physical measurement. We have developed a theory in which physical experiments that measure quantities can be used as oracles to algorithms and we have begun to classify the computational power of various forms of experiment using non-uniform complexity classes. Earlier, in Beggs et al. (2014 Reviews of Symbolic Logic7(4) 618–646), we observed that measurement can be viewed as a process of comparing a rational number z – a test quantity – with a real number y – an unknown quantity; each oracle call performs such a compar

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39

Becker, Howard. "Greg Hjorth. Classification and orbit equivalence relations. Mathematical Surveys and Monographs, vol. 75. American Mathematical Society, Providence, RI, 2000, xviii + 195 pp. - Greg Hjorth. A dichotomy theorem for turbulence. The Journal of Symbolic Logic, vol. 67 no. 4 (2002), pp. 1520–1540." Bulletin of Symbolic Logic 16, no. 3 (September 2010): 403–5. http://dx.doi.org/10.2178/bsl/1286284560.

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40

Roanes-Lozano, E., Luis M. Laita, and E. Roanes-Macias. "A Symbolic-Numeric Approach to MPL Continuous Logic and to Rule Based Expert Systems whose Underlying Logic is MPL." Open Applied Mathematics Journal 2, no. 1 (October 23, 2008): 126–33. http://dx.doi.org/10.2174/1874114200802010126.

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Wang, Rui, Wanwei Liu, Tun Li, Xiaoguang Mao, and Ji Wang. "Bounded Model Checking of ETL Cooperating with Finite and Looping Automata Connectives." Journal of Applied Mathematics 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/462532.

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As a complementary technique of the BDD-based approach, bounded model checking (BMC) has been successfully applied to LTL symbolic model checking. However, the expressiveness of LTL is rather limited, and some important properties cannot be captured by such logic. In this paper, we present a semantic BMC encoding approach to deal with the mixture ofETLfandETLl. Since such kind of temporal logic involves both finite and looping automata as connectives, all regular properties can be succinctly specified with it. The presented algorithm is integrated into the model checker ENuSMV, and the approac

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ALPUENTE, MARÍA, SANTIAGO ESCOBAR, JULIA SAPIÑA, and DEMIS BALLIS. "Symbolic Analysis of Maude Theories with Narval." Theory and Practice of Logic Programming 19, no. 5-6 (September 2019): 874–90. http://dx.doi.org/10.1017/s1471068419000243.

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AbstractConcurrent functional languages that are endowed with symbolic reasoning capabilities such as Maude offer a high-level, elegant, and efficient approach to programming and analyzing complex, highly nondeterministic software systems. Maude’s symbolic capabilities are based on equational unification and narrowing in rewrite theories, and provide Maude with advanced logic programming capabilities such as unification modulo user-definable equational theories and symbolic reachability analysis in rewrite theories. Intricate computing problems may be effectively and naturally solved in Maude

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43

ШКАРБАН, Інна. "LINGUISTIC ASPECT OF MODALITY IN MODERN MATH DISCOURSE IN ENGLISH." Проблеми гуманітарних наук. Серія Філологія, no. 49 (June 8, 2022): 231–36. http://dx.doi.org/10.24919/2522-4565.2022.49.33.

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The article reveals linguistic aspect of modality in modern math discourse in English, critically outlines a number of actual problematic issues in the area, such as the distinction between epistemic modality and evidentiality marked by formal logics philosophical grounding. General reference to previous scholarly activity in math modality research proves that it is largely based on propositional aspects of meaning. The math text corpus analysis aims to extract a set of modalities that are indispensable for formulating modal deductive reasoning. However, from a linguistic perspective academic

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Gao, Yuan, Yueling Guo, Nurul Atiqah Romli, Mohd Shareduwan Mohd Kasihmuddin, Weixiang Chen, Mohd Asyraf Mansor, and Ju Chen. "GRAN3SAT: Creating Flexible Higher-Order Logic Satisfiability in the Discrete Hopfield Neural Network." Mathematics 10, no. 11 (June 1, 2022): 1899. http://dx.doi.org/10.3390/math10111899.

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One of the main problems in representing information in the form of nonsystematic logic is the lack of flexibility, which leads to potential overfitting. Although nonsystematic logic improves the representation of the conventional k Satisfiability, the formulations of the first, second, and third-order logical structures are very predictable. This paper proposed a novel higher-order logical structure, named G-Type Random k Satisfiability, by capitalizing the new random feature of the first, second, and third-order clauses. The proposed logic was implemented into the Discrete Hopfield Neural Ne

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45

Brkić, Dejan, Pavel Praks, Renáta Praksová, and Tomáš Kozubek. "Symbolic Regression Approaches for the Direct Calculation of Pipe Diameter." Axioms 12, no. 9 (August 31, 2023): 850. http://dx.doi.org/10.3390/axioms12090850.

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This study provides novel and accurate symbolic regression-based solutions for the calculation of pipe diameter when flow rate and pressure drop (head loss) are known, together with the length of the pipe, absolute inner roughness of the pipe, and kinematic viscosity of the fluid. PySR and Eureqa, free and open-source symbolic regression tools, are used for discovering simple and accurate approximate formulas. Three approaches are used: (1) brute force of computing power, which provides results based on raw input data; (2) an improved method where input parameters are transformed through the L

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46

Qudrat-I Elahi, Khandakar. "A difficulty in Arrow’s impossibility theorem." International Journal of Social Economics 44, no. 12 (December 4, 2017): 1609–21. http://dx.doi.org/10.1108/ijse-02-2016-0065.

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Purpose The purpose of this paper is twofold. First, it evaluates the impossibility proposition, called the “Arrow impossibility theorem” (AIT), which is widely attributed to Arrow’s social choice theory. This theorem denies the possibility of arriving at any collective majority resolution in any group voting system if the social choice function must satisfy “certain natural conditions”. Second, it intends to show the reasons behind the proliferation of this impossibility impression. Design/methodology/approach Theoretical and philosophical. Findings Arrow’s mathematical model does not seem to

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Riesco, Adrián, Beatriz Santos-Buitrago, Javier De Las Rivas, Merrill Knapp, Gustavo Santos-García, and Carolyn Talcott. "Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search." BioMed Research International 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1809513.

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In biological systems, pathways define complex interaction networks where multiple molecular elements are involved in a series of controlled reactions producing responses to specific biomolecular signals. These biosystems are dynamic and there is a need for mathematical and computational methods able to analyze the symbolic elements and the interactions between them and produce adequate readouts of such systems. In this work, we use rewriting logic to analyze the cellular signaling of epidermal growth factor (EGF) and its cell surface receptor (EGFR) in order to induce cellular proliferation.

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Bylieva, D. S. "Word in technogenic multidimensional space." Philosophical Problems of IT & Cyberspace (PhilIT&C), no. 1 (August 2, 2022): 18–33. http://dx.doi.org/10.17726/philit.2022.1.2.

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Today, artificial intelligence is actively mastering natural languages, becoming an interlocutor and partner of human in various aspects of activity. However, the symbolic approach, which implies the transfer of rules and logic, has failed, the number of rules and exceptions of the language does not allow its formalization, so modern «deep learning» of artificial neural networks involves an independent search for patterns in extensive databases. During training, artificial intelligence puts a word into a sentence so that the syntagmatic relationships are as close as possible to those of the ta

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García, Víctor, Santiago Escobar, Kazuhiro Ogata, Sedat Akleylek, and Ayoub Otmani. "Modelling and verification of post-quantum key encapsulation mechanisms using Maude." PeerJ Computer Science 9 (September 19, 2023): e1547. http://dx.doi.org/10.7717/peerj-cs.1547.

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Communication and information technologies shape the world’s systems of today, and those systems shape our society. The security of those systems relies on mathematical problems that are hard to solve for classical computers, that is, the available current computers. Recent advances in quantum computing threaten the security of our systems and the communications we use. In order to face this threat, multiple solutions and protocols have been proposed in the Post-Quantum Cryptography project carried on by the National Institute of Standards and Technologies. The presented work focuses on defini

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50

Zhu, Xixi, Bin Liu, Cheng Zhu, Zhaoyun Ding, and Li Yao. "Approximate Reasoning for Large-Scale ABox in OWL DL Based on Neural-Symbolic Learning." Mathematics 11, no. 3 (January 17, 2023): 495. http://dx.doi.org/10.3390/math11030495.

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The ontology knowledge base (KB) can be divided into two parts: TBox and ABox, where the former models schema-level knowledge within the domain, and the latter is a set of statements of assertions or facts about instances. ABox reasoning is a process of discovering implicit knowledge in ABox based on the existing KB, which is of great value in KB applications. ABox reasoning is influenced by both the complexity of TBox and scale of ABox. The traditional logic-based ontology reasoning methods are usually designed to be provably sound and complete but suffer from long algorithm runtimes and do n

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