Fuzzy predicate logic for Knowledge Representation

Author

Subba Reddy, P. Venkata

Author_Institution

Dept. of Comput. Sci. & Eng., Sri Venkateswara Univ., Thirupathi, India

fYear

2013

fDate

6-8 Dec. 2013

Firstpage

43

Lastpage

48

Abstract

Sometimes AI has to deal with incomplete problems. Knowledge Representation is the main component to solve the problems in AI. Various Knowledge representation techniques are available to deal with complete information in Artificial Intelligence. The Knowledge Representation is necessary to deal with incomplete information. Many theories deal with incomplete information is based on Probable (Likelihood) where as fuzzy logic is based on the commonsense and belief. In this paper Fuzzy Knowledge Representation is proposed to deal with the incomplete information. The fuzzy propositions are transformed in to fuzzy modulations and transformed in to Fuzzy Predicate Logic (FPL). The Fuzzy Automated Reasoning is studied using Fuzzy Predicate Logic. The programming in Prolog is given for FPL.

Keywords

fuzzy logic; fuzzy set theory; knowledge representation; AI; artificial intelligence; fuzzy automated reasoning; fuzzy knowledge representation; fuzzy predicate logic; Educational institutions; Fuzzy logic; Fuzzy reasoning; Fuzzy sets; Knowledge representation; Sugar; fuzzy logic; fuzzy modules; fuzzy predicate logic; fuzzy reasoning; knowledge representation; logic programming;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Theory and Its Applications (iFUZZY), 2013 International Conference on

Conference_Location

Taipei

Type

conf

DOI

10.1109/iFuzzy.2013.6825407

Filename

6825407