Key Roles of Information Granulation and Fuzzy Logic in Human Reasoning, Concept Formulation and Computing with Words

2005 ◽  
Author(s):  
L.A. Zadeh
Keyword(s):  
Fuzzy Logic ◽  
Computing With Words ◽  
Human Reasoning ◽  
Information Granulation

A FORMALISM FOR REPRESENTING AND REASONING WITH LINGUISTIC INFORMATION

2002 ◽  
Vol 10 (03) ◽  
pp. 281-307 ◽  
Author(s):  
TRU H. CAO
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Natural Language ◽  
Functional Relation ◽  
Computing With Words ◽  
Conceptual Graphs ◽  
Graph Language ◽  
Conceptual Graph ◽  
Knowledge Representation Language ◽  
Representation Language

Conceptual graphs and fuzzy logic are two logical formalisms that emphasize the target of natural language, where conceptual graphs provide a structure of formulas close to that of natural language sentences while fuzzy logic provides a methodology for computing with words. This paper proposes fuzzy conceptual graphs as a knowledge representation language that combines the advantages of both the two formalisms for artificial intelligence approaching human expression and reasoning. Firstly, the conceptual graph language is extended with functional relation types for representing functional dependency, and conjunctive types for joining concepts and relations. Then fuzzy conceptual graphs are formulated as a generalization of conceptual graphs where fuzzy types and fuzzy attribute-values are used in place of crisp types and crisp attribute-values. Projection and join as basic operations for reasoning on fuzzy conceptual graphs are defined, taking into account the semantics of fuzzy set-based values.

Applying Fuzzy Logic and Fuzzy Methods to Marketing

2012 ◽  
pp. 1056-1068
Author(s):  
Laurent Donzé ◽  
Andreas Meier
Keyword(s):  
Fuzzy Logic ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Future Research ◽  
Computing With Words ◽  
Linguistic Variables ◽  
Research Directions ◽  
Fuzzy Methods ◽  
Future Research Directions

Marketing deals with identifying and meeting the needs of customers. It is therefore both an art and a science. To bridge the gap between art and science, soft computing, or computing with words, could be an option. This chapter introduces fundamental concepts such as fuzzy sets, fuzzy logic, and computing with linguistic variables and terms. This set of fuzzy methods can be applied in marketing and customer relationship management. In the conclusion, future research directions are given for applying fuzzy logic to marketing and customer relationship management.

Rough Sets and Approximate Reasoning

2014 ◽  
pp. 180-228 ◽  
Author(s):  
B. K. Tripathy
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Rough Sets ◽  
Intuitionistic Fuzzy Sets ◽  
Point Of View ◽  
Approximate Reasoning ◽  
Human Reasoning ◽  
Intuitionistic Fuzzy ◽  
Application Point ◽  
Future Work

Several models have been introduced to capture impreciseness in data. Fuzzy sets introduced by Zadeh and Rough sets introduced by Pawlak are two of the most popular such models. In addition, the notion of intuitionistic fuzzy sets introduced by Atanassov and the hybrid models obtained thereof have been very fruitful from the application point of view. The introduction of fuzzy logic and the approximate reasoning obtained through it are more realistic as they are closer to human reasoning. Equality of sets in crisp mathematics is too restricted from the application point of view. Therefore, extending these concepts, three types of approximate equalities were introduced by Novotny and Pawlak using rough sets. These notions were found to be restrictive in the sense that they again boil down to equality of sets and also the lower approximate equality is artificial. Keeping these points in view, three other types of approximate equalities were introduced by Tripathy in several papers. These approximate equalities were further generalised to cover the approximate equalities of fuzzy sets and intuitionistic fuzzy sets by him. In addition, considering the generalisations of basic rough sets like the covering-based rough sets and multigranular rough sets, the study has been carried out further. In this chapter, the authors provide a comprehensive study of all these forms of approximate equalities and illustrate their applicability through several examples. In addition, they provide some problems for future work.

A Fuzzy Logic-Based Approach for Supporting Decision-Making Process in B2C Electronic Commerce Transaction

2011 ◽  
pp. 1416-1429
Author(s):  
Fahim Akhter ◽  
Zakaria Maamar ◽  
Dave Hobbs
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Electronic Commerce ◽  
Decision Process ◽  
Human Reasoning ◽  
Critical Factors ◽  
Human Decision Process ◽  
Human Decision ◽  
Business To Consumer ◽  
B2c Electronic Commerce

The purpose of this article is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This article uncovers some of the hidden relationships between critical factors such as security, familiarity, design, and competitiveness. We analyze the effect of these factors on human decision process and how they affect the Business-to-Consumer (B2C) outcome when they are used collectively. This research provides a toolset for B2C vendors to access and evaluate a user’s transaction decision process and also an assisted reasoning tool for the online user.

A Fuzzy Logic-Based Approach for Supporting Decision-Making Process in B2C Electronic Commerce Transaction

2009 ◽  
pp. 258-271
Author(s):  
Fahim Akhter ◽  
Zakaria Maamar ◽  
Dave Hobbs
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Electronic Commerce ◽  
Decision Process ◽  
Human Reasoning ◽  
Critical Factors ◽  
Human Decision Process ◽  
Human Decision ◽  
Business To Consumer ◽  
B2c Electronic Commerce

The purpose of this article is to present an application of fuzzy logic to human reasoning about electronic commerce (e-commerce) transactions. This article uncovers some of the hidden relationships between critical factors such as security, familiarity, design, and competitiveness. We analyze the effect of these factors on human decision process and how they affect the Business- to-Consumer (B2C) outcome when they are used collectively. This research provides a toolset for B2C vendors to access and evaluate a user’s transaction decision process and also an assisted reasoning tool for the online user.

Fuzzy Logic in the Broad Sense

2017 ◽  
Author(s):  
Radim Bělohlávek ◽  
Joseph W. Dauben ◽  
George J. Klir
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Human Reasoning ◽  
Human Beings ◽  
Real Numbers ◽  
New Directions ◽  
Gradual Development

The chapter begins by introducing the important and useful distinction between the research agendas of fuzzy logic in the narrow and the broad senses. The chapter deals with the latter agenda, whose ultimate goal is to employ intuitive fuzzy set theory for emulating commonsense human reasoning in natural language and other unique capabilities of human beings. Restricting to standard fuzzy sets, whose membership degrees are real numbers in the unit interval [0,1], the chapter describes how this broad agenda has become increasingly specific via the gradual development of standard fuzzy set theory and the associated fuzzy logic. An overview of currently recognized nonstandard fuzzy sets, which open various new directions in fuzzy logic, is presented in the last section of this chapter.

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