The General Nilpotent System

Similar documents
A special class of fuzzy operators and its application in modelling effects and decision problems

On the Intersections of QL-Implications with (S, N)- and R-Implications

Left-continuous t-norms in Fuzzy Logic: an Overview

Interval Valued Fuzzy Sets from Continuous Archimedean. Triangular Norms. Taner Bilgic and I. Burhan Turksen. University of Toronto.

(S, N)- and R-implications: A state-of-the-art survey

Analysis of additive generators of fuzzy operations represented by rational functions


Kybernetika. Michał Baczyński; Balasubramaniam Jayaram Yager s classes of fuzzy implications: some properties and intersections

On the Law of Importation. in Fuzzy Logic. J.Balasubramaniam, Member IEEE. Abstract

Kybernetika. Margarita Mas; Miquel Monserrat; Joan Torrens QL-implications versus D-implications. Terms of use:

Aggregation and Non-Contradiction

A Deep Study of Fuzzy Implications

Fuzzy Implications: Some Recently Solved Problems

TRIANGULAR NORMS WITH CONTINUOUS DIAGONALS

Continuous R-implications

Directional Monotonicity of Fuzzy Implications

The Domination Relation Between Continuous T-Norms

Triple Rotation: Gymnastics for T-norms

Comparison of Fuzzy Operators for IF-Inference Systems of Takagi-Sugeno Type in Ozone Prediction

Construction of Functions by Fuzzy Operators

Conditionally distributive real semirings

Fuzzy Sets. Mirko Navara navara/fl/fset printe.pdf February 28, 2019

Construction of Interval-valued Fuzzy Preference Relations from Ignorance Functions and Fuzzy Preference Relations. Application to Decision Making

Function Construction with Fuzzy Operators

Optimization with Max-Min Fuzzy Relational Equations

Fuzzy logic Fuzzyapproximate reasoning

Some examples of generated fuzzy implicators

Residuated fuzzy logics with an involutive negation

Aggregation functions: construction methods, conjunctive, disjunctive and mixed classes

Generalized continuous and left-continuous t-norms arising from algebraic semantics for fuzzy logics

(, q)-fuzzy Ideals of BG-algebras with respect to t-norm

2.2: Logical Equivalence: The Laws of Logic

The problem of distributivity between binary operations in bifuzzy set theory

CONSERVATIVE AND DISSIPATIVE FOR T-NORM AND T-CONORM AND RESIDUAL FUZZY CO-IMPLICATION

ASSOCIATIVE n DIMENSIONAL COPULAS

GENERATED FUZZY IMPLICATIONS IN FUZZY DECISION MAKING

The Sigmoidal Approximation of Łukasiewicz Operators

Characterizations of fuzzy implications satisfying the Boolean-like law y I(x, y)

Fuzzy Sets and Fuzzy Techniques. Sladoje. Introduction. Operations. Combinations. Aggregation Operations. An Application: Fuzzy Morphologies

Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems

AN ALGEBRAIC STRUCTURE FOR INTUITIONISTIC FUZZY LOGIC

arxiv: v1 [math.gm] 20 Oct 2014

Propositional Calculus: Formula Simplification, Essential Laws, Normal Forms

Implication functions in interval-valued fuzzy set theory

Averaging Operators on the Unit Interval

EXTRACTING FUZZY IF-THEN RULE BY USING THE INFORMATION MATRIX TECHNIQUE WITH QUASI-TRIANGULAR FUZZY NUMBERS

Approximation and interpolation sum of exponential functions

Fuzzy Answer Set semantics for Residuated Logic programs

On L-fuzzy syntopogeneous structures

Intuitionistic Fuzzy Sets - An Alternative Look

Extending the Monoidal T-norm Based Logic with an Independent Involutive Negation

When does a semiring become a residuated lattice?

CSC Discrete Math I, Spring Propositional Logic

Reducing t-norms and augmenting t-conorms

Logic: Propositional Logic (Part I)

Discrete Structures for Computer Science

FURTHER DEVELOPMENT OF CHEBYSHEV TYPE INEQUALITIES FOR SUGENO INTEGRALS AND T-(S-)EVALUATORS

Towards logics for neural conceptors

QUANTUM STRUCTURES AND FUZZY SET THEORY

Lecture Notes in Real Analysis Anant R. Shastri Department of Mathematics Indian Institute of Technology Bombay

THE INTERVAL CONSTRUCTOR ON CLASSES OF ML-ALGEBRAS

S-MEASURES, T -MEASURES AND DISTINGUISHED CLASSES OF FUZZY MEASURES

Introduction to Sets and Logic (MATH 1190)

PHIL12A Section answers, 16 February 2011

MV-algebras and fuzzy topologies: Stone duality extended

Description Logics. Foundations of Propositional Logic. franconi. Enrico Franconi

Propositional natural deduction

Understanding (dis)similarity measures

Examples. Example (1) Example (2) Let x, y be two variables, and denote statements p : x = 0 and q : y = 1. Solve. x 2 + (y 1) 2 = 0.

Copyright c 2007 Jason Underdown Some rights reserved. statement. sentential connectives. negation. conjunction. disjunction

Chapter I: Introduction to Mathematical Fuzzy Logic

UPPER AND LOWER SET FORMULAS: RESTRICTION AND MODIFICATION OF THE DEMPSTER-PAWLAK FORMALISM

DE MORGAN TRIPLES REVISITED

CISC-102 Fall 2018 Week 11

CISC-102 Winter 2016 Lecture 17

MATH 409 Advanced Calculus I Lecture 12: Uniform continuity. Exponential functions.

1.3 Propositional Equivalences

What is Logic? Introduction to Logic. Simple Statements. Which one is statement?

(T; N) and Residual Fuzzy Co-Implication in Dual Heyting Algebra with Applications

2. The Logic of Compound Statements Summary. Aaron Tan August 2017

Lecture 2. Econ August 11

MULTICRITERIA DECISION MAKING IN BALANCED MODEL OF FUZZY SETS

On Fuzzy Negations and Automorphisms

On Interval Fuzzy Negations

On Common Fixed Point for Single and Set-Valued Maps Satisfying OWC Property in IFMS using Implicit Relation

Comparison of two versions of the Ferrers property of fuzzy interval orders

Domination of Aggregation Operators and Preservation of Transitivity

Practice Test III, Math 314, Spring 2016

It rains now. (true) The followings are not propositions.

Generalised Atanassov Intuitionistic Fuzzy Sets

On (Weighted) k-order Fuzzy Connectives

A Fuzzy Formal Logic for Interval-valued Residuated Lattices

Compound Propositions

De Morgan Systems on the Unit Interval

1.1 Language and Logic

Some Pre-filters in EQ-Algebras

A Common Fixed Point Theorems in Menger(PQM) Spaces with Using Property (E.A)

On the filter theory of residuated lattices

Fuzzy Systems. Fuzzy Sets and Fuzzy Logic

Logic and Discrete Mathematics. Section 3.5 Propositional logical equivalence Negation of propositional formulae

Transcription:

The General Nilpotent System József Dombi 1,2 Orsolya Csiszár 1 1 Óbuda University, Budapest, Hungary 2 University of Szeged, Hungary FSTA, Liptovský Ján, 2014 csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 1 / 30

Outline 1 Motivation and background 2 Basic preliminaries Negations Triangular norms and conorms Nilpotent operators 3 Connective Systems Notations Consistency 4 Results Bounded Systems Examples 5 Conclusion and further work csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 2 / 30

Motivation and background

Motivation and background Nilpotent Connective Systems Fuzzy set theory Proper choice of fuzzy connectives Nilpotent operators Nilpotent t-norms and t-conorms: preferable properties Operators Systems Instead of pure operators, we examine connective SYSTEMS Our results Consistent nilpotent connective systems which are not isomorphic to Lukasiewicz system csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 4 / 30

Basic preliminaries

Basic preliminaries Negations Negations Definition A decreasing function n(x) : [0,1] [0,1] is a fuzzy negation, if n(0) = 1 and n(1) = 0. Definition A fuzzy negation is strict, if it is strictly decreasing and continuous strong, if it is involutive, i.e. n(n(x)) = x for x [0,1]. Trillas theorem n(x) is a strong negation if and only if n(x) = f n (x) 1 (1 f n (x)), where f n (x) : [0,1] [0,1] is continuous and strictly increasing. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 6 / 30

Basic preliminaries Triangular norms and conorms Triangular norms and conorms (Schweizer and Sklar, 1960) t-norm T (Conjunction) A t-norm T is a function on [0,1] 2 that satisfies, for all x,y,z [0,1]: T(x,1) = x (neutral element 1); x y T(x,z) T(y,z) (monotonicity); T(x,y) = T(y,x) (commutativity); T(T(x,y),z) = T(x,T(y,z)) (associativity). t-conorm S (Disjunction) S(x,0) = x (neutral element 0) plus the other three properties above. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 7 / 30

Basic preliminaries Triangular norms and conorms Representable t-norms and t-conorms A continuous t-norm T is said to be Archimedean if T(x,x) < x holds for all x (0,1), strict if T is strictly monotone i.e. T(x,y) < T(x,z) whenever x [0,1] and y < z, and nilpotent if there exist x,y (0,1) such that T(x,y) = 0. A continuous t-conorm S is said to be Archimedean if S(x,x) > x holds for every x,y (0,1), strict if S is strictly monotone i.e. S(x,y) < S(x,z) whenever x [0,1] and y < z, and nilpotent if there exist x,y (0,1) such that S(x,y) = 1. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 8 / 30

Basic preliminaries Triangular norms and conorms Additive generators A function T : [0,1] 2 [0,1] is a continuous Archimedean t-norm iff it has a continuous additive generator, i.e. there exists a continuous strictly decreasing function t : [0,1] [0, ] with t(1) = 0, which is uniquely determined up to a positive multiplicative constant, such that T(x,y) = t 1 (min(t(x)+t(y),t(0)), x,y [0,1]. (1) A function S : [0,1] 2 [0,1] is a continuous Archimedean t-conorm iff it has a continuous additive generator, i.e. there exists a continuous strictly increasing function s : [0,1] [0, ] with s(0) = 0, which is uniquely determined up to a positive multiplicative constant, such that S(x,y) = s 1 (min(s(x)+s(y),s(1)), x,y [0,1]. (2) csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 9 / 30

Basic preliminaries Triangular norms and conorms Additive generators A t-norm T is strict if and only if t(0) =. A t-norm T is nilpotent if and only if t(0) <. A t-conorm S is strict if and only if s(1) =. A t-conorm S is nilpotent if and only if s(1) <. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 10 / 30

Basic preliminaries Nilpotent operators Nilpotent operators Preferable Properties = T L (x,y) = max(x+y 1,0) = S L (x,y) = min(x +y,1) Law of contradiction c(x,n(x)) = 0 Excluded middle d(x,n(x)) = 1 Coincidence of residual and S-implications... csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 11 / 30

Basic preliminaries Nilpotent operators Notations Normalized generator functions uniquely determined f c (x) := t(x) t(0), f d(x) := s(x) s(1). f c (x),f d (x),f n (x) : [0,1] [0,1]. Cutting operation 0 if x < 0 [x] = x if 0 x 1 1 if 1 < x csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 12 / 30

Basic preliminaries Nilpotent operators Cutting function c(x,y) = f 1 c [f c (x)+f c (y)] d(x,y) = f 1 d [f d (x)+f d (y)] Min(x,y) = f 1 c [f c (x)+[f c (y) f c (x)]] Max(x,y) = n ( f 1 c [f c (n(x))+[f c (n(y)) f c (n(x))]] ) T L (x,y) = [x +y 1] S L (x,y) = [x +y] csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 13 / 30

Connective Systems

Connective Systems Notations Connective Systems strong negation n(x) conjunction c(c, y) disjunction d(x, y) Definition The triple (c(x,y),d(x,y),n(x)), where c(x,y) is a t-norm, d(x,y) is a t-conorm and n(x) is a strong negation, is called a connective system. Definition A connective system is nilpotent, if the conjunction is a nilpotent t-norm, and the disjunction is a nilpotent t-conorm. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 15 / 30

Connective Systems Notations Definition Two connective systems (c 1 (x,y),d 1 (x,y),n 1 (x)) and (c 2 (x,y),d 2 (x,y),n 2 (x)) are isomorphic, if there exists a bijection φ : [0,1] [0,1] such that φ 1 (c 1 (φ(x),φ(y))) = c 2 (x,y) φ 1 (d 1 (φ(x),φ(y))) = d 2 (x,y) φ 1 (n 1 (φ(x))) = n 2 (x) Definition A connective system is called Lukasiewicz system, if it is isomorphic to ([x +y 1],[x +y],1 x), i.e. it has the form (φ 1 [φ(x)+φ(y) 1],φ 1 [φ(x)+φ(y)],φ 1 [1 φ(x)]). csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 16 / 30

Connective Systems Consistency Consistency of Connective Systems Classification Property: law of contradiction: excluded middle: c(x,n(x)) = 0, d(x,n(x)) = 1. De Morgan Laws: c(n(x),n(y)) = n(d(x,y)) or d(n(x),n(y)) = n(c(x,y)). csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 17 / 30

Connective Systems Consistency IS IT SENSIBLE TO USE MORE THAN ONE GENERATOR FUNCTIONS? csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 18 / 30

Results

Results Bounded Systems Nilpotent Connective Systems Among nilpotent systems, Lukasiewicz connective system (T L,S L, standard negation) is characterized by f c (x)+f d (x) = 1, x [0,1]. For f c (x)+f d (x) < 1, x [0,1]: the system is not consistent. For f c (x)+f d (x) > 1, x [0,1]: BOUNDED SYSTEMS BOUNDED SYSTEM fc+ fd> 1 fc(x) fd(x) ukasiewicz logic C ukasiewicz logic D csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 20 / 30

Results Bounded Systems Bounded Systems Three different negations 1.0 0.8 0.6 0.4 0.2 0.2 0.4 0.6 0.8 1.0 n d (x) = f 1 d (1 f d (x)) < n(x) < n c (x) = f 1 c (1 f c (x)). f c (x)+f d (x) = 1 n c (x) = n(x) = n d (x) csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 21 / 30

Results Bounded Systems Consistency Theorem In a connective structure the classification property holds if and only if n d (x) n(x) n c (x), x [0,1]. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 22 / 30

Results Bounded Systems Consistency Theorem In a connective structure the classification property holds if and only if n d (x) n(x) n c (x), x [0,1]. Theorem In a connective system the De Morgan law holds if and only if n(x) = f 1 c (f d (x)) = f 1 d (f c (x)), x [0,1]. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 22 / 30

Results Bounded Systems Consistency 1 If c(x,y),d(x,y) and n(x) fulfil the De Morgan identity and the classification property (i.e. they form a consitent system), then f c (x)+f d (x) 1, x [0,1]. 2 If f c (x)+f d (x) 1, x [0,1] and the De Morgan law holds, then the classification property also holds (which now means that the system is consistent). csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 23 / 30

Results Examples Example for f c (x)+f d (x) > 1 For f c (x) := 1 x α,f d (x) := 1 (1 x) α,n(x) := 1 x, α (1, ). the connective system is consistent, f c (x)+f d (x) > 1, x [0,1] (or equivalently n d (x) < n(x) < n c (x), x [0,1]). csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 24 / 30

Results Examples Rational generators For the Dombi functions (from pliant systems ) f n (x) = f c (x) = 1 1+ ν 1 x 1 ν x 1 1+ νc 1 ν c x 1 x 1 f d (x) = 1+ ν d 1 x 1 ν d x the following statements are equivalent: 1 The connective structure defined by the Dombi functions satisfies the De Morgan law. 2 ( 1 ν ν ) 2 = ν c 1 ν c 1 ν d ν d. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 25 / 30

Results Examples Rational generators For the Dombi functions (from pliant systems ) f n (x) = f c (x) = 1 1+ ν 1 x 1 ν x 1 1+ νc 1 ν c x 1 x 1 f d (x) = 1+ ν d 1 x 1 ν d x the following statements are equivalent: 1 n d (x) < n(x) < n c (x) 2 ν d < ν < ν c 3 Given that the De Morgan property holds, f c (x)+f d (x) > 1, or equivalently ν c +ν d < 1. csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 26 / 30

Results Examples Examples Rational generators ν c = 0.6 and ν d = 0.4 ν c = 0.4 and ν d = 0.2 csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 27 / 30

Conclusion and further work

Conclusion and further work Conclusion and further work Consistent nilpotent connective systems using more than one generator functions (not new operators, new system) f c (x)+f d (x) > 1 n d (x) < n(x) < n c (x) 2 naturally derived thresholds (ν c,ν d ) Further work: implication, equivalence csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 29 / 30

Conclusion and further work Life is like riding a bicycle. To keep your balance you must keep moving. /Einstein/ csiszar.orsolya@nik.uni-obuda.hu The General Nilpotent System FSTA, 2014 30 / 30 THANK YOU FOR YOUR ATTENTION!