Results for 'Fuzzy logic'

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  1. Fuzzy Logic and Higher-Order Vagueness.Nicholas J. J. Smith - 2011 - In Petr Cintula, Chris Fermüller, Lluis Godo & Petr Hájek (eds.), Logical Models of Reasoning with Vague Information. pp. 1--19.
    The major reason given in the philosophical literature for dissatisfaction with theories of vagueness based on fuzzy logic is that such theories give rise to a problem of higherorder vagueness or artificial precision. In this paper I first outline the problem and survey suggested solutions: fuzzy epistemicism; measuring truth on an ordinal scale; logic as modelling; fuzzy metalanguages; blurry sets; and fuzzy plurivaluationism. I then argue that in order to decide upon a solution, we (...)
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  2. Fuzzy logic theory and applications: Part I and Part II.Lotfi A. Zadeh - 2018 - New Jersey: World Scientific. Edited by R. A. Aliev.
    part 1. Fuzzy logic theory 1 -- part 2. Applications and advanced topics of fuzzy logic.
     
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  3.  8
    Fuzzy logics – quantitatively.Marek Zaionc & Zofia Kostrzycka - 2023 - Journal of Applied Non-Classical Logics 34 (1):97-132.
    ABSTRACT The Gödel–Dummett logic and Łukasiewicz one are two main many-valued logics used by the fuzzy logic community. Our goal is a quantitative comparison of these two. In this paper, we will mostly consider the 3-valued Gödel–Dummett logic as well as the 3-valued Łukasiewicz one. We shall concentrate on their implicational-negation fragments which are limited to formulas formed with a fixed finite number of variables. First, we investigate the proportion of the number of true formulas of (...)
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    Fuzzy logic: applications in artificial intelligence, big data, and machine learning.Lefteri H. Tsoukalas - 2023 - New York: McGraw Hill.
    This hands-on guide offers clear explanations of fuzzy logic along with practical uses and detailed examples. Written by an award-winning engineer and experienced author, Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning is aimed at improving competence and skills in students and professionals alike. Inside, you will discover how to apply fuzzy logic and migrate to a new man-machine relationship in the context of pervasive digitization and big data across emerging technologies. (...)
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  5.  5
    Fuzzy logic-based material selection and synthesis.Mustafa B. Babanli - 2018 - New Jersey: World Scientific.
    This unique compendium presents a comprehensive and self-contained theory of material development under imperfect information and its applications. The book describes new approaches to synthesis and selection of materials with desirable characteristics. Such approaches provide the ability of systematic and computationally effective analysis in order to predict composition, structure and related properties of new materials. The volume will be a useful advanced textbook for graduate students. It is also suitable for academicians and practitioners who wish to have fundamental models in (...)
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  6.  8
    Introduction to fuzzy logic.James K. Peckol - 2021 - Hoboken, NJ: Wiley.
    Fuzzy logic is finding increased application in the control of real-world processes and in the work with and the manipulation of inexact knowledge. Two of the major attractions of fuzzy logic are: it permits one to express problems in (familiar) linguistic terms and it can be applied where the numerical mathematical model of a system may be too complex or impossible to build using conventional techniques. This book, written in an easily accessible style, assumes that students (...)
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  7. Fuzzy logic and approximate reasoning.L. A. Zadeh - 1975 - Synthese 30 (3-4):407-428.
    The term fuzzy logic is used in this paper to describe an imprecise logical system, FL, in which the truth-values are fuzzy subsets of the unit interval with linguistic labels such as true, false, not true, very true, quite true, not very true and not very false, etc. The truth-value set, , of FL is assumed to be generated by a context-free grammar, with a semantic rule providing a means of computing the meaning of each linguistic truth-value (...)
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  8.  38
    Residuated fuzzy logics with an involutive negation.Francesc Esteva, Lluís Godo, Petr Hájek & Mirko Navara - 2000 - Archive for Mathematical Logic 39 (2):103-124.
    Residuated fuzzy logic calculi are related to continuous t-norms, which are used as truth functions for conjunction, and their residua as truth functions for implication. In these logics, a negation is also definable from the implication and the truth constant $\overline{0}$ , namely $\neg \varphi$ is $\varphi \to \overline{0}$. However, this negation behaves quite differently depending on the t-norm. For a nilpotent t-norm (a t-norm which is isomorphic to Łukasiewicz t-norm), it turns out that $\neg$ is an involutive (...)
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  9.  71
    Substructural Fuzzy Logics.George Metcalfe & Franco Montagna - 2007 - Journal of Symbolic Logic 72 (3):834 - 864.
    Substructural fuzzy logics are substructural logics that are complete with respect to algebras whose lattice reduct is the real unit interval [0.1]. In this paper, we introduce Uninorm logic UL as Multiplicative additive intuitionistic linear logic MAILL extended with the prelinearity axiom ((A → B) ∧ t) ∨ ((B → A) ∧ t). Axiomatic extensions of UL include known fuzzy logics such as Monoidal t-norm logic MTL and Gödel logic G, and new weakening-free logics. (...)
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  10.  57
    Fuzzy logic and arithmetical hierarchy III.Petr Hájek - 2001 - Studia Logica 68 (1):129-142.
    Fuzzy logic is understood as a logic with a comparative and truth-functional notion of truth. Arithmetical complexity of sets of tautologies and satisfiable sentences as well of sets of provable formulas of the most important systems of fuzzy predicate logic is determined or at least estimated.
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  11.  43
    Fuzzy logic and nursing.Eun-Ok Im & Wonshik Chee - 2003 - Nursing Philosophy 4 (1):53-60.
    In empiricism, there are only two answers for a question: black or white. Yet, subjective meanings of human behaviours and responses toward health and illness cannot be simply explained with black and white. Gray zones are needed because they are characterized by complexity and require a contextual understanding. In this paper, we present and suggest fuzzy logic as an example of theoretical bases that help transcend the conflicts between objectivity and subjectivity, respect gray zones between black and white (...)
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  12.  85
    Fuzzy logics based on [0,1)-continuous uninorms.Dov Gabbay & George Metcalfe - 2007 - Archive for Mathematical Logic 46 (5-6):425-449.
    Axiomatizations are presented for fuzzy logics characterized by uninorms continuous on the half-open real unit interval [0,1), generalizing the continuous t-norm based approach of Hájek. Basic uninorm logic BUL is defined and completeness is established with respect to algebras with lattice reduct [0,1] whose monoid operations are uninorms continuous on [0,1). Several extensions of BUL are also introduced. In particular, Cross ratio logic CRL, is shown to be complete with respect to one special uninorm. A Gentzen-style hypersequent (...)
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  13. Many-Valued And Fuzzy Logic Systems From The Viewpoint Of Classical Logic.Ekrem Sefa Gül - 2018 - Tasavvur - Tekirdag Theology Journal 4 (2):624 - 657.
    The thesis that the two-valued system of classical logic is insufficient to explanation the various intermediate situations in the entity, has led to the development of many-valued and fuzzy logic systems. These systems suggest that this limitation is incorrect. They oppose the law of excluded middle (tertium non datur) which is one of the basic principles of classical logic, and even principle of non-contradiction and argue that is not an obstacle for things both to exist and (...)
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  14.  37
    Why Fuzzy Logic?Petr Hájek - 2006 - In Dale Jacquette (ed.), A Companion to Philosophical Logic. Oxford, UK: Blackwell. pp. 595–605.
    This chapter contains sections titled: Origin Many‐Valued Logic Fuzzy Logic in a Broad and Narrow Sense The Basic Fuzzy Propositional Calculus The Basic Fuzzy Predicate Calculus Similarity The Liar and Dequotation Very True Probability Conclusion.
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  15.  51
    Mathematical fuzzy logics.Siegfried Gottwald - 2008 - Bulletin of Symbolic Logic 14 (2):210-239.
    The last decade has seen an enormous development in infinite-valued systems and in particular in such systems which have become known as mathematical fuzzy logics. The paper discusses the mathematical background for the interest in such systems of mathematical fuzzy logics, as well as the most important ones of them. It concentrates on the propositional cases, and mentions the first-order systems more superficially. The main ideas, however, become clear already in this restricted setting.
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  16. Intuitionistic fuzzy logic and intuitionistic fuzzy set theory.Gaisi Takeuti & Satoko Titani - 1984 - Journal of Symbolic Logic 49 (3):851-866.
  17.  11
    Fuzzy Logic and Mathematics: A Historical Perspective.Radim Bělohlávek, Joseph W. Dauben & George J. Klir - 2017 - Oxford, England and New York, NY, USA: Oxford University Press. Edited by Joseph Warren Dauben & George J. Klir.
    The term "fuzzy logic," as it is understood in this book, stands for all aspects of representing and manipulating knowledge based on the rejection of the most fundamental principle of classical logic---the principle of bivalence. According to this principle, each declarative sentence is required to be either true or false. In fuzzy logic, these classical truth values are not abandoned. However, additional, intermediate truth values between true and false are allowed, which are interpreted as degrees (...)
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  18.  8
    Using fuzzy logic: towards intelligent systems.Jun Yan - 1994 - New York: Prentice-Hall. Edited by Michael Ryan & James Power.
    A clear account of the principles of fuzzy logic-based design, from a computer/electronics engineering perspective. This pedagogical work incorporates current fuzzy logic techniques, emphasizing hardware/software design for fuzzy systems and fuzzy logic development tools.
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  19. Fuzzy Logic.Kazem Sadegh-Zadeh - 2nd ed. 2015 - In Handbook of Analytic Philosophy of Medicine. Springer Verlag.
    Medical knowledge as well as clinical practice are characterized by inescapable uncertainty. There are many reasons this is the case, but foremost among them is that almost everything in medicine is inevitably vague, be it something linguistic such as the term “illness”, or something extra-linguistic such as the condition referred to as illness. If we ask ourselves, then, what the term “illness” means exactly, on the one hand; and how we may precisely delimit the condition illness, on the other; we (...)
     
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  20.  34
    Δ-core Fuzzy Logics with Propositional Quantifiers, Quantifier Elimination and Uniform Craig Interpolation.Franco Montagna - 2012 - Studia Logica 100 (1-2):289-317.
    In this paper we investigate the connections between quantifier elimination, decidability and Uniform Craig Interpolation in Δ-core fuzzy logics added with propositional quantifiers. As a consequence, we are able to prove that several propositional fuzzy logics have a conservative extension which is a Δ-core fuzzy logic and has Uniform Craig Interpolation.
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  21. Fuzzy Logics in Theories of Vagueness.Nicholas J. J. Smith - 2015 - In Petr Cintula, Christian Fermüller & Carles Noguera (eds.), Handbook of Mathematical Fuzzy Logic - Volume 3. College Publications.
  22.  19
    Fuzzy logic and fuzzy set theory.Gaisi Takeuti & Satoko Titani - 1992 - Archive for Mathematical Logic 32 (1):1-32.
  23.  8
    Fuzzy logic and restricted quantifiers.James D. McCawley - 1980 - In Stig Kanger & Sven Öhman (eds.), Philosophy and Grammar. Reidel. pp. 101--118.
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  24.  21
    Fuzzy logics – quantitatively.Zofia Kostrzycka & Marek Zaionc - 2023 - Journal of Applied Non-Classical Logics 34 (1):97-132.
    The Gödel–Dummett logic and Łukasiewicz one are two main many-valued logics used by the fuzzy logic community. Our goal is a quantitative comparison of these two. In this paper, we will mostly consider the 3-valued Gödel–Dummett logic as well as the 3-valued Łukasiewicz one. We shall concentrate on their implicational-negation fragments which are limited to formulas formed with a fixed finite number of variables. First, we investigate the proportion of the number of true formulas of a (...)
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  25.  33
    On Fuzzy Logic I Many‐valued rules of inference.Jan Pavelka - 1979 - Mathematical Logic Quarterly 25 (3‐6):45-52.
  26.  40
    On Fuzzy Logic I Many‐valued rules of inference.Jan Pavelka - 1979 - Mathematical Logic Quarterly 25 (3-6):45-52.
  27. Fuzzy logic and applications: 9th International Workshop, WILF 2011, Trani, Italy, August 29-31, 2011: proceedings.Anna Maria Fanelli, Witold Pedrycz & Alfredo Petrosino (eds.) - 2011 - Heidelberg: Springer.
     
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  28.  45
    Fuzzy logic and arithmetical hierarchy, II.Petr Hájek - 1997 - Studia Logica 58 (1):129-141.
    A very simple many-valued predicate calculus is presented; a completeness theorem is proved and the arithmetical complexity of some notions concerning provability is determined.
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  29.  32
    On Fuzzy Logic III. Semantical completeness of some many‐valued propositional calculi.Jan Pavelka - 1979 - Mathematical Logic Quarterly 25 (25‐29):447-464.
  30.  59
    Adaptive fuzzy logics for contextual hedge interpretation.Stephan van der Waart van Gulik - 2009 - Journal of Logic, Language and Information 18 (3):333-356.
    The article presents several adaptive fuzzy hedge logics. These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically, strictly speaking or loosely speaking, or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information concerning the meaning (...)
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  31.  34
    On Fuzzy Logic III. Semantical completeness of some many-valued propositional calculi.Jan Pavelka - 1979 - Zeitschrift fur mathematische Logik und Grundlagen der Mathematik 25 (25-29):447-464.
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  32.  16
    ‎Proof Theory for Fuzzy Logics.George Metcalfe, Nicola Olivetti & Dov M. Gabbay - 2008 - Dordrecht, Netherland: Springer.
    Fuzzy logics are many-valued logics that are well suited to reasoning in the context of vagueness. They provide the basis for the wider field of Fuzzy Logic, encompassing diverse areas such as fuzzy control, fuzzy databases, and fuzzy mathematics. This book provides an accessible and up-to-date introduction to this fast-growing and increasingly popular area. It focuses in particular on the development and applications of "proof-theoretic" presentations of fuzzy logics; the result of more than (...)
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  33.  79
    Fuzzy Logic Programming and Fuzzy Control.Giangiacomo Gerla - 2005 - Studia Logica 79 (2):231-254.
    We show that it is possible to base fuzzy control on fuzzy logic programming. Indeed, we observe that the class of fuzzy Herbrand interpretations gives a semantics for fuzzy programs and we show that the fuzzy function associated with a fuzzy system of IF-THEN rules is the fuzzy Herbrand interpretation associated with a suitable fuzzy program.
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  34. An introduction to fuzzy logic for practical applications.Kazuo Tanaka - 1997 - New York: Springer.
    Fuzzy logic has become an important tool for a number of different applications ranging from the control of engineering systems to artificial intelligence. In this concise introduction, the author presents a succinct guide to the basic ideas of fuzzy logic, fuzzy sets, fuzzy relations, and fuzzy reasoning, and shows how they may be applied. The book culminates in a chapter which describes fuzzy logic control: the design of intelligent control systems using (...)
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  35. Fuzzy logic: A key to shared wisdom.Vladimir Dimitrov - unknown
    The ancient mythology could serve as an effective medium for metaphorically conveying complex concepts and principles to a broad spectrum of people. In this paper we show how the fuzzy logic approach can be used to translate the metaphoric language of ancient myths and legends into a 'soft' scientific paradigm which helps us to understand better the social complexity of our time.
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  36.  51
    Mathematical Fuzzy Logic – What It Can Learn from Mostowski and Rasiowa.Petr Hájek - 2006 - Studia Logica 84 (1):51-62.
    Important works of Mostowski and Rasiowa dealing with many-valued logic are analyzed from the point of view of contemporary mathematical fuzzy logic.
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  37.  18
    The fuzzy logic of chaos and probabilistic inference.I. Antoniou & Z. Suchanecki - 1997 - Foundations of Physics 27 (3):333-362.
    The logic of a physical system consists of the elementary observables of the system. We show that for chaotic systems the logic is not any more the classical Boolean lattice but a kind of fuzzy logic which we characterize for a class of chaotic maps. Among other interesting properties the fuzzy logic of chaos does not allow for infinite combinations of propositions. This fact reflects the instability of dynamics and it is shared also by (...)
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  38. Deviant logic, fuzzy logic: beyond the formalism.Susan Haack - 1974 - Chicago: University of Chicago Press. Edited by Susan Haack.
    Initially proposed as rivals of classical logic, alternative logics have become increasingly important in areas such as computer science and artificial intelligence. Fuzzy logic, in particular, has motivated major technological developments in recent years. Susan Haack's Deviant Logic provided the first extended examination of the philosophical consequences of alternative logics. In this new volume, Haack includes the complete text of Deviant Logic , as well as five additional papers that expand and update it. Two of (...)
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  39.  54
    Fuzzy logic.Petr Hajek - 2008 - Stanford Encyclopedia of Philosophy.
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  40.  21
    Mathematics Behind Fuzzy Logic.Esko Turunen - 1999 - Physica-Verlag Heidelberg.
    Many results in fuzzy logic depend on the mathematical structure the truth value set obeys. In this textbook the algebraic foundations of many-valued and fuzzy reasoning are introduced. The book is self-contained, thus no previous knowledge in algebra or in logic is required. It contains 134 exercises with complete answers, and can therefore be used as teaching material at universities for both undergraduated and post-graduated courses. Chapter 1 starts from such basic concepts as order, lattice, equivalence (...)
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  41. Fuzzy logic: Mathematical tools for approximate reasoning.Giangiacomo Gerla - 2003 - Bulletin of Symbolic Logic 9 (4):510-511.
     
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  42.  28
    On Fuzzy Logic II. Enriched residuated lattices and semantics of propositional calculi.Jan Pavelka - 1979 - Mathematical Logic Quarterly 25 (7‐12):119-134.
  43.  55
    Structural Completeness in Fuzzy Logics.Petr Cintula & George Metcalfe - 2009 - Notre Dame Journal of Formal Logic 50 (2):153-182.
    Structural completeness properties are investigated for a range of popular t-norm based fuzzy logics—including Łukasiewicz Logic, Gödel Logic, Product Logic, and Hájek's Basic Logic—and their fragments. General methods are defined and used to establish these properties or exhibit their failure, solving a number of open problems.
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  44.  36
    Fuzzy Logic and Strategic Management: An Application of Ragin’s Fuzzy-Set Methods.Özlem Öz - 2005 - Philosophy of Management 5 (1):55-66.
    The main purpose of this article is to bring Ragin’s recent methodological contributions, which build on ideas borrowed from fuzzy logic, to the attention of management scholars. To demonstrate the possible use of the techniques developed by Ragin in management research, three specific examples for their likely applications are presented: the replications of Porter’s diamond framework for Turkey, Greece and Canada. The article concludes that Ragin’s systematic techniques prove helpful in making explicit the process of comparing qualitative evidence (...)
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  45.  27
    On Fuzzy Logic II. Enriched residuated lattices and semantics of propositional calculi.Jan Pavelka - 1979 - Mathematical Logic Quarterly 25 (7-12):119-134.
  46.  23
    Fuzzy logic, continuity and effectiveness.Loredana Biacino & Giangiacomo Gerla - 2002 - Archive for Mathematical Logic 41 (7):643-667.
    It is shown the complete equivalence between the theory of continuous (enumeration) fuzzy closure operators and the theory of (effective) fuzzy deduction systems in Hilbert style. Moreover, it is proven that any truth-functional semantics whose connectives are interpreted in [0,1] by continuous functions is axiomatizable by a fuzzy deduction system (but not by an effective fuzzy deduction system, in general).
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  47.  3
    Adaptive Fuzzy Logics for Contextual Hedge Interpretation.Stephan Waart van Gulik - 2009 - Journal of Logic, Language and Information 18 (3):333-356.
    The article presents several adaptive fuzzy hedge logics. These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically, strictly speaking or loosely speaking, or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information concerning the meaning (...)
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  48. Adaptive fuzzy logics for contextual hedge interpretation.Stephan der Waart van Gulivank - 2009 - Journal of Logic, Language and Information 18 (3).
    The article presents several adaptive fuzzy hedge logics . These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically , strictly speaking or loosely speaking , or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information (...)
     
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  49.  7
    Can Fuzzy Logic Help to Pose Some Problems in the Philosophy of Science?Alejandro Sobrino & Enric Trillas - 1997 - Poznan Studies in the Philosophy of the Sciences and the Humanities 61:277-300.
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  50.  6
    The fuzzy logical model of perception: A teaspoon for a pyramid.Robert F. Port - 1989 - Behavioral and Brain Sciences 12 (4):773-774.
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