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From Computing With Numbers To Computing With Words From Manipulation Of Measurements To Manipulation of Perceptions
 Appl. Math. Comput. Sci
"... Computing, in its usual sense, is centered on manipulation of numbers and symbols. In contrast, computing with words, or CW for short, is a methodology in which the objects of computation are words and propositions drawn from a natural language, e.g., small, large, far, heavy, not very likely, the p ..."
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Cited by 111 (4 self)
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Computing, in its usual sense, is centered on manipulation of numbers and symbols. In contrast, computing with words, or CW for short, is a methodology in which the objects of computation are words and propositions drawn from a natural language, e.g., small, large, far, heavy, not very likely, the price of gas is low and declining, Berkeley is near San Francisco, it is very unlikely that there will be a significant increase in the price of oil in the near future, etc. Computing with words is inspired by the remarkable human capability to perform a wide variety of physical and mental tasks without any measurements and any computations. Familiar examples of such tasks are parking a car, driving in heavy traffic, playing golf, riding a bicycle, understanding speech and summarizing a story. Underlying this remarkable capability is the brain’s crucial ability to manipulate perceptions – perceptions of distance, size, weight, color, speed, time, direction, force, number, truth, likelihood and other characteristics of physical and mental objects. Manipulation of perceptions plays a key role in human recognition, decision and execution processes. As a methodology, computing with words provides a foundation for a computational theory of perceptions – a theory which may have an important bearing on how humans make – and machines might make – perceptionbased rational decisions in an environment of imprecision, uncertainty and partial truth. A basic difference between perceptions and measurements is that, in general, measurements are crisp whereas perceptions are fuzzy. One of the fundamental aims of science has been and continues to be that of progressing from perceptions to measurements. Pursuit of this aim has led to brilliant successes. We have sent men to the moon; we can build computers
A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (fourth edition)
, 2005
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A Treatise on ManyValued Logics
 Studies in Logic and Computation
, 2001
"... The paper considers the fundamental notions of many valued logic together with some of the main trends of the recent development of infinite valued systems, often called mathematical fuzzy logics. Besides this logical approach also a more algebraic approach is discussed. And the paper ends with som ..."
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Cited by 64 (4 self)
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The paper considers the fundamental notions of many valued logic together with some of the main trends of the recent development of infinite valued systems, often called mathematical fuzzy logics. Besides this logical approach also a more algebraic approach is discussed. And the paper ends with some hints toward applications which are based upon actual theoretical considerations about infinite valued logics. Key words: mathematical fuzzy logic, algebraic semantics, continuous tnorms, leftcontinuous tnorms, Pavelkastyle fuzzy logic, fuzzy set theory, nonmonotonic fuzzy reasoning 1 Basic ideas 1.1 From classical to manyvalued logic Logical systems in general are based on some formalized language which includes a notion of well formed formula, and then are determined either semantically or syntactically. That a logical system is semantically determined means that one has a notion of interpretation or model 1 in the sense that w.r.t. each such interpretation every well formed formula has some (truth) value or represents a function into
Integration of featural information in speech perception
 Psychological Review
"... A model for the identification of speech sounds is proposed that assumes that (a) the acoustic cues are perceived independently, (b) feature evaluation provides information about the degree to which each quality is present in the speech sound, (c) each speech sound is denned by a propositional proto ..."
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Cited by 58 (11 self)
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A model for the identification of speech sounds is proposed that assumes that (a) the acoustic cues are perceived independently, (b) feature evaluation provides information about the degree to which each quality is present in the speech sound, (c) each speech sound is denned by a propositional prototype in longterm memory that determines how the featural information is integrated, and (d) the speech sound is identified on the basis of the relative degree to which it matches the various alternative prototypes. The model was supported by the results of an experiment in which subjects identified stopconsonantvowel syllables that were factorially generated by independently varying acoustic cues for voicing and for place of articulation. This experiment also replicated previous findings of changes in the identification boundary of one acoustic dimension as a function of the level of another dimension. These results have previously been interpreted as evidence for the interaction of the perceptions of the acoustic features themselves. In contrast, the present model provides a good description of the data, including these boundary changes, while still maintaining complete
Models of integration given multiple sources of information
 Psychol. Rev
, 1990
"... Several models of information integration are developed and analyzed within the context ofa prototypical patternrecognition task. The central concerns are whether the models prescribe maximally efficient (optimal) integration and to what extent the models are psychologically valid. Evaluation, inte ..."
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Cited by 55 (17 self)
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Several models of information integration are developed and analyzed within the context ofa prototypical patternrecognition task. The central concerns are whether the models prescribe maximally efficient (optimal) integration and to what extent the models are psychologically valid. Evaluation, integration, and decision processes are specified for each model. Important features are whether evaluation is noisy, whether integration follows Bayes's theorem, and whether decision consists of a criterion rule or a relative goodness rule. Simulations of the models and predictions of the results by the same models are carried out to provide a measure of identifiability or the extent to which the models can be distinguished from one another. The models are also contrasted against empirical results from tasks with 2 and 4 response alternatives and with graded responses. Conceptual Framework There is a growing consensus that behavior reflects the influence of multiple sources of information. Auditory and visual perception, reading and speech perception, and decision making and judgment are modulated by a wide variety of influences
What is a Forest? On the vagueness of certain geographic concepts
 Topoi
, 2002
"... The paper examines ways in which the meanings of geographical concepts are affected by the phenomenon of vagueness. A logical analysis based on the theory of supervaluation semantics is developed and employed to describe differences and logical dependencies between different senses of vague concepts ..."
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Cited by 33 (3 self)
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The paper examines ways in which the meanings of geographical concepts are affected by the phenomenon of vagueness. A logical analysis based on the theory of supervaluation semantics is developed and employed to describe differences and logical dependencies between different senses of vague concepts. Particular attention is given to analysing the concept of `forest' which exhibits many kinds of vagueness.
A Logical Approach To Interpolation Based On Similarity Relations
, 1996
"... One of the possible semantics of fuzzy sets is in terms of similarity, namely a grade of membership of an item in a fuzzy set can be viewed as the degree of resemblance between this item and prototypes of the fuzzy set. In such a framework, an interesting question is how to devise a logic of similar ..."
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Cited by 26 (10 self)
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One of the possible semantics of fuzzy sets is in terms of similarity, namely a grade of membership of an item in a fuzzy set can be viewed as the degree of resemblance between this item and prototypes of the fuzzy set. In such a framework, an interesting question is how to devise a logic of similarity, where inference rules can account for the proximity between interpretations. The aim is to capture the notion of interpolation inside a logical setting. In this paper, we investigate how a logic of similarity dedicated to interpolation can be defined, by considering different natural consequence relations induced by the presence of a similarity relation on the set of interpretations. These consequence relations are axiomatically characterized in a way that parallels the characterization of nonmonotonic consequence relationships. It is shown how to reconstruct the similarity relation underlying a given family of consequence relations that obey the axioms. Our approach strikingly differs ...
Social and Semiotic Analyses for Theorem Prover User Interface Design
 Formal Aspects of Computing
, 1999
"... We describe an approach to user interface design based on ideas from social science, narratology (the theory of stories), cognitive science, and a new area called algebraic semiotics. Social analysis helps to identify certain roles for users with their associated requirements, and suggests ways to m ..."
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Cited by 19 (11 self)
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We describe an approach to user interface design based on ideas from social science, narratology (the theory of stories), cognitive science, and a new area called algebraic semiotics. Social analysis helps to identify certain roles for users with their associated requirements, and suggests ways to make proofs more understandable, while algebraic semiotics, which combines semiotics with algebraic specification, provides rigorous theories for interface functionality and for a certain technical notion of quality. We apply these techniques to designing user interfaces for a distributed cooperative theorem proving system, whose main component is a website generation and proof assistance tool called Kumo. This interface integrates formal proving, proof browsing, animation, informal explanation, and online background tutorials, drawing on a richer than usual notion of proof. Experience with using the interface is reported, and some conclusions are drawn.
FUZZY SETS: HISTORY AND BASIC NOTIONS
"... This paper is an introduction to fuzzy set theory. It has several purposes. First, it tries to explain the emergence of fuzzy sets from an historical perspective. Looking back to the history of sciences, it seems that fuzzy sets were bound to appear at some point in the 20th century. Indeed, Zadeh&a ..."
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Cited by 14 (0 self)
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This paper is an introduction to fuzzy set theory. It has several purposes. First, it tries to explain the emergence of fuzzy sets from an historical perspective. Looking back to the history of sciences, it seems that fuzzy sets were bound to appear at some point in the 20th century. Indeed, Zadeh's works have cristalized and popularized a concern that has appeared in the first half of the century, mainly in philosophical circles. Another purpose of the paper is to scan the basic definitions in the field, that are required for a proper reading of the rest of the volume, as well as the other volumes of the Handbooks of Fuzzy Sets Series. This Chapter also contains a discussion on operational semantics of the generally too abstract notion of membership function. Lastly, a survey of variants of fuzzy sets and related matters is provided.