DocumentCode :
2618632
Title :
Fuzzy quantifiers and quantifying operators in a connectionist expert system development tool
Author :
Romaniuk, Steve G. ; Hall, Lawrence O.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
fYear :
1991
fDate :
18-21 Nov 1991
Firstpage :
134
Abstract :
The authors give information pertaining to the implementation of fuzzy quantifiers and quantifying operators within a connectionist network model. The operators described can be extended to arbitrary input size, by retaining similar overall behavior. Examples are given to show the responses one would obtain when modifying the belief in the inputs. These outputs correspond to responses one would intuitively expect. The importance of having been able to implement these constructs is given in the possibility of formulating more natural-language-like constructs. In conjunction with learning, complex symbolic systems may be modeled in domains which contain significant imprecision in a connectionist network using the technique considered. The methods could also be adapted to other connectionist architectures
Keywords :
expert systems; fuzzy logic; natural languages; neural nets; belief; complex symbolic systems; connectionist architectures; connectionist expert system development tool; connectionist network model; fuzzy logic; fuzzy quantifiers; learning; natural-language-like constructs; quantifying operators; Computer science; Expert systems; Fuzzy logic; Fuzzy reasoning; Fuzzy systems; Hybrid intelligent systems; Instruction sets; Knowledge representation; Natural languages; Recruitment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
Type :
conf
DOI :
10.1109/IJCNN.1991.170393
Filename :
170393
Link To Document :
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