Masters Theses

Abstract

"This research is primarily concerned with increasing the performance of expert systems. A refined focus of attention strategy and its affect on performance are discussed. Early expert systems used a brute force approach to process the knowledge base. Each production rule in the knowledge base was evaluated each cycle. More recently, processing efficiency has been increased by focusing the attention of the inference engine on a subset of the rules by "filtering" for further testing, only rules that could possibly fire given the current content of the context base. Focus of attention as developed in this research increases performance over filtering systems by further narrowing the focus of attention of the inference engine, down to the subexpression level. Positive results are reported"--Abstract, page iii.

Advisor(s)

Dekock, Arlan R.

Committee Member(s)

Prater, John Bruce, 1932-2002
Kluczny, Raymond Michael

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

1984

Pagination

vii, 49 pages

Note about bibliography

Includes bibliographical references (page 48).

Rights

© 1984 Kevin Wayne Whiting, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

Expert systems (Computer science)Database managementData mining

Thesis Number

T 5116

Print OCLC #

11299387

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