An overview of fuzzy quantifiers. (II). Reasoning and applications

Abstract In the second part of the overview, reasoning with fuzzily defined quantifiers and applications are presented. Possibility based reasoning is summarized in detail. The widely used quantifier extension principle and various reasoning schemas derived from it are discussed. Some disadvantages of the quantifier extension principle are pointed out. Although intervalvalued quantifiers are only a special case of general quantifiers, some specific properties and results arise from them. Furthermore, they suggest another approach to interence with fuzzy quantifiers. Reasoning with quantification and several kinds of qualification is introduced. This kind of reasoning requires a seamless synthesis of probability theory, possibility theory, fuzzy logic and belief theory. At last, the applications of fuzzily defined quantifiers in decision making and fuzzy database systems are introduced.

[1]  Drew McDermott,et al.  Non-Monotonic Logic I , 1987, Artif. Intell..

[2]  Daniel G. Schwartz,et al.  On the semantics for qualified syllogisms , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[3]  Madan M. Gupta,et al.  Approximate reasoning in expert systems , 1985 .

[4]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[5]  Zbigniew W. Ras,et al.  Methodologies for Intelligent Systems , 1991, Lecture Notes in Computer Science.

[6]  Ronald R. Yager Automated Multiagent Preference Aggregation Using Fuzzy Quantifiers , 1995, ICMAS.

[7]  H. J. Skala,et al.  Aspects of vagueness , 1984 .

[8]  Ronald R. Yager,et al.  General Multiple-Objective Decision Functions and Linguistically Quantified Statements , 1984, Int. J. Man Mach. Stud..

[9]  Ping-Yu Hsu,et al.  Improving SQL with generalized quantifiers , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[10]  N. Rescher Many Valued Logic , 1969 .

[11]  Lotfi A. Zadeh,et al.  A Theory of Approximate Reasoning , 1979 .

[12]  L. N. Kanal,et al.  Uncertainty in Artificial Intelligence 5 , 1990 .

[13]  Trevor P Martin,et al.  AI and Computer Power , 1994 .

[14]  Ebrahim H. Mamdani,et al.  Fuzzy sets and applications: selected papers by L A Zadeh, R R Yager, S Ovchinikov, R M Tong, H T Nguyen (eds) John Wiley and Sons Inc, £45.85, ISBN 0 471 85710 6, 684pp , 1988, Knowl. Based Syst..

[15]  Ronald R. Yager,et al.  REASONING WITH FUZZY QUANTIFIED STATEMENTS: PART II , 1985 .

[16]  Lotfi A. Zadeh,et al.  A theory of commonsense knowledge , 1983 .

[17]  Bernadette Bouchon-Meunier,et al.  Fuzzy Logic And Soft Computing , 1995 .

[18]  Ronald R. Yager,et al.  On implementing usual values , 1986, UAI.

[19]  Ronald R. Yager,et al.  On usual values in commonsense reasoning , 1989 .

[20]  Janusz Kacprzyk,et al.  A Generalization of Discounted Multistage Decision Making andControl Through Fuzzy Linguistic Quantifiers: An Attempt to Introduce Commonsense Knowledge , 1986 .

[21]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[22]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[23]  Francisco Herrera,et al.  Aggregation operators for linguistic weighted information , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[24]  L. Zadeh,et al.  Fuzzy sets and applications : selected papers , 1987 .

[25]  L. Zadeh The role of fuzzy logic in the management of uncertainty in expert systems , 1983 .

[26]  Francisco Herrera,et al.  ON GROUP DECISION MAKING UNDER LINGUISTIC PREFERENCES AND FUZZY LINGUISTIC QUANTIFIERS , 1995 .

[27]  L. Zadeh A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL LANGUAGES , 1983 .

[28]  Patrick Bosc,et al.  On the Interpretation of Set-Oriented Fuzzy Quantified Queries and Their Evaluation in a Database Management System , 1993, ISMIS.

[29]  Didier Dubois,et al.  On fuzzy syllogisms , 1988, Comput. Intell..

[30]  V. Novák Fuzzy sets and their applications , 1989 .

[31]  Daniel G. Schwartz,et al.  Dynamic Reasoning with Qualified Syllogisms , 1997, Artif. Intell..

[32]  Patrick Bosc,et al.  On the evaluation of fuzzy quantified queries in a database management system , 1992 .

[33]  Lotfi A. Zadeh,et al.  Syllogistic reasoning in fuzzy logic and its application to usuality and reasoning with dispositions , 1985, IEEE Transactions on Systems, Man, and Cybernetics.