A methodology for the development of expert systems is proposed and developed. Expert systems are examined and classified into three major groups. The imprecision inherent in many expert's domains is addressed with the use of fuzzy set theory. Fuzzy relations are used for knowledge representation and the inference process. Knowledge acquisition is also addressed in the relational context. All aspects of the system may be seen in the context of fuzzy relations which provide a powerful consistency. The developed methodology allows the construction of an expert system which has no domain knowledge built into it. This allows the system to be used in different domains with only the knowledge base being updated. We have applied the methodology to develop a multi-knowledge source expert system which incorporates fuzzy reasoning techniques. A blackboard is used for communication and the system may be distributed across several processors. Successful examples of the systems operation are shown. / Source: Dissertation Abstracts International, Volume: 47-05, Section: B, page: 2059. / Thesis (Ph.D.)--The Florida State University, 1986.
Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_75827 |
Contributors | HALL, LAWRENCE O'HIGGINS., Florida State University |
Source Sets | Florida State University |
Detected Language | English |
Type | Text |
Format | 211 p. |
Rights | On campus use only. |
Relation | Dissertation Abstracts International |
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