USING META-PROGRAMMING, CONSTRAINT LOGIC PROGRAMMING AND APPROXIMATE REASONING FOR EXPERT SYSTEMS DESIGN
This paper presents an enhancement of the CARESS system-A Constraint Approximative Reasoning System Support-introduced in (Popescu and Roventa, 1994). CARESS is an experimental system with primarily two objectives: (1)knowledge representation and manipulation techniques and to implement them in PROL...
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| Veröffentlicht in: | International journal of general systems Jg. 28; H. 2-3; S. 243 - 258 |
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| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Taylor & Francis Group
01.08.1999
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| ISSN: | 0308-1079, 1563-5104 |
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| Abstract | This paper presents an enhancement of the CARESS system-A Constraint Approximative Reasoning System Support-introduced in (Popescu and Roventa, 1994). CARESS is an experimental system with primarily two objectives:
(1)knowledge representation and manipulation techniques and to implement them in PROLOG III, and
(2) to develop a knowledge programming environment for building expert systems. We discuss here the use of meta-programming, constraint logic programming and approximate reasoning for the design of expert systems
It has already been proven that meta-programming and logic programming are powerful techniques for expert system design. Fuzzy logic can be used to model one kind of uncertainty. Constraint logic programming is useful for dealing with the constraints given by operations using fuzzy sets. |
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| AbstractList | This paper presents an enhancement of the CARESS system-A Constraint Approximative Reasoning System Support-introduced in (Popescu and Roventa, 1994). CARESS is an experimental system with primarily two objectives:
(1)knowledge representation and manipulation techniques and to implement them in PROLOG III, and
(2) to develop a knowledge programming environment for building expert systems. We discuss here the use of meta-programming, constraint logic programming and approximate reasoning for the design of expert systems
It has already been proven that meta-programming and logic programming are powerful techniques for expert system design. Fuzzy logic can be used to model one kind of uncertainty. Constraint logic programming is useful for dealing with the constraints given by operations using fuzzy sets. |
| Author | ROVENTA, EUGENE |
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| Cites_doi | 10.1145/79204.79210 10.1016/0165-0114(87)90110-2 10.1016/0743-1066(89)90034-4 10.1007/978-3-642-69391-5_13 10.1109/TSMC.1980.4308391 10.1007/978-3-642-83189-8 10.1016/0888-613X(93)90010-B |
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| References | Kandel A. (CIT0006) 1992 Giarratano J. (CIT0004) 1993 CIT0010 Pedrycz W. (CIT0012) 1991 CIT0001 Lloyd J. (CIT0009) 1987 Klir G.J. (CIT0007) 1988 Rowe N.C. (CIT0014) 1988 Kowalski R. (CIT0008) 1979 Popescu I. (CIT0013) 1995 Sterling L. (CIT0016) 1986 CIT0002 Geiger C. (CIT0003) 1994 CIT0005 CIT0015 CIT0018 CIT0017 Pedrycz W. (CIT0011) 1993 Yager R. (CIT0019) 1987 |
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| SubjectTerms | approximate reasoning constraint logic programming Expert system meta-programming prolog |
| Title | USING META-PROGRAMMING, CONSTRAINT LOGIC PROGRAMMING AND APPROXIMATE REASONING FOR EXPERT SYSTEMS DESIGN |
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