From interval probability theory to computable fuzzy first-order logic and beyond

Author

Buehrer, Daniel J.

Author_Institution

Inst. of Comput. Sci. & Inf. Eng., Nat. Chung Cheng Univ., Chia Yi, Taiwan

fYear

1994

fDate

26-29 Jun 1994

Firstpage

1428

Abstract

This paper first presents a simple explanation for the min/max bounds which are used in interval probability theory (IPT), possibility theory, fuzzy rough sets, and vague logic. Based on this definition, a computable version of first-order fuzzy logic is defined, where all of the upper bounds for instances of a theorem and its negation are guaranteed to eventually be listed. Based on this fuzzy logic, a complete version of fuzzy Prolog is defined. This fuzzy Prolog is then used to give some examples of fuzzy Prolog definitions of fuzzy concepts such as fuzzy linguistic variables, fuzzy modifiers, fuzzy quantifiers, and various kinds of fuzzy norms and conorms

Keywords

PROLOG; fuzzy logic; fuzzy set theory; possibility theory; probability; computable fuzzy first-order logic; first-order fuzzy logic; fuzzy Prolog; fuzzy linguistic variables; fuzzy logic; fuzzy modifiers; fuzzy quantifiers; fuzzy rough sets; interval probability theory; min/max bounds; negation; possibility theory; upper bounds; vague logic; Boolean algebra; Computer science; Fuzzy logic; Fuzzy set theory; Possibility theory; Probabilistic logic; Rough sets; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1896-X

Type

conf

DOI

10.1109/FUZZY.1994.343608

Filename

343608