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2015, Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
We present and analyze inference method called Perception-based Logical Deduction (PbLD) aimed at the treatment of fuzzy IF-THEN rules as linguistically expressed genuine logical implications. Besides the original PbLD, we propose a new balancing variant of PbLD, introduce both variants with fuzzy inputs and study them from the point of view of the interpolativity property.
International Journal of Intelligent Systems, 2004
In this article, we return to the problem of the derivation of a conclusion on the basis of fuzzy IF–THEN rules. The so-called Mamdani method is well elaborated and widely applied. In this article, we present an alternative to it. The fuzzy IF–THEN rules are here interpreted as genuine linguistic sentences consisting of the so-called evaluating linguistic expressions. Sets of fuzzy IF–THEN rules are called linguistic descriptions. Linguistic expressions derived on the basis of an observation in a concrete context are called perceptions. Together with the linguistic description, they can be used in logical deduction, which we will call a perception-based logical deduction. We focus on semantics only and confine ourselves to one specific model. If the perception-based deduction is repeated and the result interpreted in an appropriate model, we obtain a piecewise continuous and monotonous function. Though the method has already proved to work well in many applications, the nonsmoothness of the output may sometimes lead to problems. We propose in this article a method for how the resulting function can be made smooth so that the output preserves its good properties. The idea consists of postprocessing the output using a special fuzzy approximation method called F-transform. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 1007–1031, 2004.
2016
We present and analyze inference method called Perception-based Logical Deduction (PbLD) aimed at the treatment of fuzzy IF-THEN rules as linguis-tically expressed genuine logical implications. Be-sides the original PbLD, we propose a new balanc-ing variant of PbLD, introduce both variants with fuzzy inputs and study them from the point of view of the interpolativity property.
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2004
This paper presents an approach to approximate reasoning over a set of IF-THEN rules called fuzzy logic deduction. It understands IF-THEN rules as linguistically expressed logical implications and interprets them inside formal logical theory. Methodology and some properties are presented.
A perception-based logical deduction is formulated in the frame of fuzzy intensional logic. We will show that under certain conditions, this kind of deduction is also a universal approximator.
1986
The generalized modus ponens is a fuzzy logic pattern of reasoning that permits to make inferences with rules having imprecision both in their antecedent and consequent parts. Though it is a very powerful approximate reasoning tool (from a theoretical point of view), this technique may result in unacceptably slow executions if inappropriately implemented. There are several ways to avoid the inefficiency bottleneck. One of them, that is the object of this paper, consists in introducing an approximation technique focussing only of what is semantically important. This approximation technique is conceived so as to be used in situations where the dependency between two given variables is described via a collection of rules. Moreover, this paper addresses the problem in the setting having the main features that follow: the possibility distributions involved in facts and rules are continuous (the referential is the real line), normalized, unimodal and expressed by parametrized functions; only single antecedent rules are considered; the rules are consistent and it is assumed that their antecedents and consequents do not overlap too much; the deduction process is based on the ‘min’ conjunction and Gödel implication operators. The ultimate goal of this work is to render the generalized modus ponens technique usable in practical deduction systems.
Zeitschrift für Mathematische Logik und Grundlagen der Mathematik, 1990
International Journal of Industrial Mathematics, 2015
This paper deals with one problem that needs to be addressed in the emerging field known under the name computing with perceptions. It is the problem of describing, approximately, a given fuzzy set in natural language. This problem has lately been referred to as the problem of retranslation. An approaches to dealing with the retranslation problem is discussed in the paper, that is based on a pre-defined set of linguistic terms and the associated fuzzy sets. The retranslation problem is discussed in terms of two criteria validity and informativeness.
Soft Computing, 1999
This paper presents a new linguistic approximation algorithm and its implementation in the frame of fuzzy logic deduction. The algorithm presented is designed for fuzzy logic deduction mechanism implemented in Linguistic Fuzzy Logic Controller (LFLC).
Lectures on Soft Computing and Fuzzy Logic, 2001
Intuitionistic fuzzy logic IF was introduced by Takeuti and Titani. This logic coincides with the first-order Gödel logic based on the real unit interval [0, 1] as set of truth-values. We present a natural deduction system NIF for IF . NIF is defined by suitably translating a first-order extension of Avron's hypersequent calculus for Gödel logic. Soundness, completeness and normal form theorems for NIF are provided.
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011), 2011
In this paper we will investigate which fuzzy/linguistic rules are redundant in systems of such rules called linguistic descriptions. We present a formal definition of redundancy and show that rules which are seemingly redundant can be in fact indispensable. These results apply for IF-THEN rules which use evaluative linguistic expressions (e.g., small, very big, etc.) and inference method called perception-based logical deduction (PbLD). However, they are also valid for inference systems which use compatible design choices with PbLD.
Fuzzy Sets and Systems, 1997
Rules of inference in fuzzy sentential logic are studied, in particular, some instances of fuzzy rule of inference are established. An example of how to apply these rules is given.
Elsevier eBooks, 1993
In much of human reasoning, the form of reasoning is approximate rather than exact as in "A red apple is ripe and this apple is more or less red. Then this apple is more or less ripe.' L.A. Zadeh and E.H. Mamdani suggested methods for such a fuzzy reasoning as an application of fuzzy set theory. The method involves an inference rule and a conditional proposition which contains fuzzy concepts. In this paper we point out that the consequence inferred by their methods does not always fit our intuitions and we suggest the improved methods which fit our intuitions under several criteria.
2015
The approaches to the solution of various problems of artificial intelligence methods are proposed. In particular, the problem of knowledge representation by means of fuzzy specifications in expert systems, the problem of recognizing the structures of the proteins of different organization levels and the problem of building linguistic models in fuzzy Boolean variables logic are considered. All methods are based on the ideas of inductive mathematics. To investigate a reliability of these methods is possible only with the help of the theory of probability or possibility theory.
Journal of Mathematics
The crucial role that fuzzy implications play in many applicable areas was our motivation to revisit the topic of them. In this paper, we apply classical logic’s laws such as De Morgan’s laws and the classical law of double negation in known formulas of fuzzy implications. These applications lead to new families of fuzzy implications. Although a duality in properties of the preliminary and induced families is expected, we will prove that this does not hold, in general. Moreover, we will prove that it is not ensured that these applications lead us to fuzzy implications, in general, without restrictions. We generate and study three induced families, the so-called D ′ -implications, QL ′ -implications, and R ′ -implications. Each family is the “closest” to its preliminary-“creator” family, and they both are simulating the same (or a similar) way of classical thinking.
Lecture Notes in Computer Science, 2005
Conditional deduction in binary logic basically consists of deriving new statements from an existing set of statements and conditional rules. Modus Ponens, which is the classical example of a conditional deduction rule, expresses a conditional relationship between an antecedent and a consequent. A generalisation of Modus Ponens to probabilities in the form of probabilistic conditional inference is also well known. This paper describes a method for conditional deduction with beliefs which is a generalisation of probabilistic conditional inference and Modus Ponens. Meaningful conditional deduction requires a degree of relevance between the antecedent and the consequent, and this relevance can be explicitly expressed and measured with our method. Our belief representation has the advantage that it is possible to represent partial ignorance regarding the truth of statements, and is therefore suitable to model typical real life situations. Conditional deduction with beliefs thereby allows partial ignorance to be included in the analysis and deduction of statements and hypothesis.
Fuzzy Modus Ponens (FMP) and Fuzzy Modus Tollens (FMT) are two fundamental patterns of approximate reasoning. Suppose A and B are fuzzy predicates and ''IF A THEN B'' is a fuzzy rule. Approximate reasoning often requires to derive an approximation B Ã of B from a given approximation A Ã of A, or vice versa. To solve these problems, Zadeh introduces the well-known Compositional Rule of Inference (CRI), which models fuzzy rule by implication and computes B Ã (A Ã , resp.) by composing A Ã (B Ã , resp.) with A ! B. Wang argues that the use of the compositional operation is logically not sufficiently justified and proposes the Triple Implication Principle (TIP) instead. Both CRI and TIP do not explicitly use the closeness of A and A Ã (or that of B and B Ã ) in the process of calculating the consequence, which makes the thus computed approximation sometimes useless or misleading.
Fuzzy Sets and Systems, 2001
An approach to fuzzy control based on fuzzy logic in narrow sense (fuzzy inference rules + fuzzy set of logical axioms) is proposed. This gives an interesting theoretical framework and suggests new tools for fuzzy control.
IFSA World Congress and 20th NAFIPS …, 2001
Symmetry
In this paper we introduce a new method of generating fuzzy implications via known fuzzy implications. We focus on the case of generating fuzzy implications via a fuzzy connective and at least one known fuzzy implication. We present some basic desirable properties of fuzzy implications that are invariant via this method. Furthermore, we suggest some ways of preservation or violation of these properties, based in this method. We show how we can generate not greater or not weaker fuzzy implications with specific properties. Finally, two subclasses of any fuzzy implication arise, the so called T and S subclasses.
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