113 research outputs found

    An approach for linguistic multi-attribute decision making based on linguistic many-valued logic

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    There are various types of multi-attribute decision-making (MADM) problems in our daily lives and decision-making problems under uncertain environments with vague and imprecise information involved. Therefore, linguistic multi-attribute decision-making problems are an important type studied extensively. Besides, it is easier for decision-makers to use linguistic terms to evaluate/choose among alternatives in real life. Based on the theoretical foundation of the Hedge algebra and linguistic many-valued logic, this study aims to address multi-attribute decision-making problems by linguistic valued qualitative aggregation and reasoning method. In this paper, we construct a finite monotonous Hedge algebra for modeling the linguistic information related to MADM problems and use linguistic many-valued logic for deducing the outcome of decision making. Our method computes directly on linguistic terms without numerical approximation. This method takes advantage of linguistic information processing and shows the benefit of Hedge algebra

    A classical degree-theoretic treatment of the sorites paradox : master's thesis in philosophy

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    Since 1970s, degree-of-truth theory has been proposed as a solution to the Sorites paradox. However, one perennial attack to degree-of-truth theory is that its logic - fuzzy logic - is non-classical. Inspired by Gödel (1933), I attempt to better degree-of-truth theory by classicalizing it. That is, I attempt to give an interpretation of fuzzy logic within classical logic enriched by degree operators {⚪, ◔, ◑, ◕, ⚫} - “it is of no/low/moderate/high/full degree that …”. Intuitively, degree-of-truth is classicalized as classical bivalent truth-value and a largely independent notion of degrees. A formal semantics of this enriched classical logic is presented, from which two semantic consequences are derived. The two semantic consequences are applied to analyse the (in)validity of the Sorites argument. There are two results: 1. the validity of the standard Sorites argument is reasserted, 2. a new argument for the invalidity of the degreed version of the Sorites argument is presented.https://www.ester.ee/record=b5239778*es

    A logical approach to fuzzy truth hedges

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    The starting point of this paper are the works of Hájek and Vychodil on the axiomatization of truth-stressing and-depressing hedges as expansions of Hájek's BL logic by new unary connectives. They showed that their logics are chain-complete, but standard completeness was only proved for the expansions over Gödel logic. We propose weaker axiomatizations over an arbitrary core fuzzy logic which have two main advantages: (i) they preserve the standard completeness properties of the original logic and (ii) any subdiagonal (resp. superdiagonal) non-decreasing function on [0, 1] preserving 0 and 1 is a sound interpretation of the truth-stresser (resp. depresser) connectives. Hence, these logics accommodate most of the truth hedge functions used in the literature about of fuzzy logic in a broader sense. © 2013 Elsevier Inc. All rights reserved.The authors acknowledge partial support of the MICINN projects TASSAT (TIN2010-20967-C04-01) and ARINF (TIN2009-14704-C03-03), and the FP7-PEOPLE-2009-IRSES project MaToMUVI (PIRSES-GA-2009-247584). Carles Noguera also acknowledges support of the research contract “Juan de la Cierva” JCI-2009-05453.Peer Reviewe

    Lotfi A. Zadeh: On the man and his work

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    AbstractZadeh is one of the most impressive thinkers of the current time. An engineer by formation, although the range of his scientific interests is very broad, this paper only refers to his work towards reaching computation, mimicking ordinary reasoning, expressed in natural language, namely, with the introduction of fuzzy sets, fuzzy logic, and soft computing, as well as more recently, computing with words and perceptions

    Resolution in Linguistic Propositional Logic based on Linear Symmetrical Hedge Algebra

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    The paper introduces a propositional linguistic logic that serves as the basis for automated uncertain reasoning with linguistic information. First, we build a linguistic logic system with truth value domain based on a linear symmetrical hedge algebra. Then, we consider G\"{o}del's t-norm and t-conorm to define the logical connectives for our logic. Next, we present a resolution inference rule, in which two clauses having contradictory linguistic truth values can be resolved. We also give the concept of reliability in order to capture the approximative nature of the resolution inference rule. Finally, we propose a resolution procedure with the maximal reliability.Comment: KSE 2013 conferenc

    On the semantics of fuzzy logic

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    AbstractThis paper presents a formal characterization of the major concepts and constructs of fuzzy logic in terms of notions of distance, closeness, and similarity between pairs of possible worlds. The formalism is a direct extension (by recognition of multiple degrees of accessibility, conceivability, or reachability) of the najor modal logic concepts of possible and necessary truth.Given a function that maps pairs of possible worlds into a number between 0 and 1, generalizing the conventional concept of an equivalence relation, the major constructs of fuzzy logic (conditional and unconditioned possibility distributions) are defined in terms of this similarity relation using familiar concepts from the mathematical theory of metric spaces. This interpretation is different in nature and character from the typical, chance-oriented, meanings associated with probabilistic concepts, which are grounded on the mathematical notion of set measure. The similarity structure defines a topological notion of continuity in the space of possible worlds (and in that of its subsets, i.e., propositions) that allows a form of logical “extrapolation” between possible worlds.This logical extrapolation operation corresponds to the major deductive rule of fuzzy logic — the compositional rule of inference or generalized modus ponens of Zadeh — an inferential operation that generalizes its classical counterpart by virtue of its ability to be utilized when propositions representing available evidence match only approximately the antecedents of conditional propositions. The relations between the similarity-based interpretation of the role of conditional possibility distributions and the approximate inferential procedures of Baldwin are also discussed.A straightforward extension of the theory to the case where the similarity scale is symbolic rather than numeric is described. The problem of generating similarity functions from a given set of possibility distributions, with the latter interpreted as defining a number of (graded) discernibility relations and the former as the result of combining them into a joint measure of distinguishability between possible worlds, is briefly discussed

    Fuzzy logic, deductive rules of inference and linguistic reasoning on knowledge base

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    In this paper we introduce a notion of knowledge base consisting of statements with truth degree in which every statement may have several truth degrees. A set of rules of inference handling this kind of statements, a deductive reasoning method based on  these rules will be considered. The consistency of the knowledge base will be also investigated
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