Masters Theses

Title

A focus of attention algorithm for expert systems

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, leaf 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 leaves

Note about bibliography

Includes bibliographical references (leaf 48).

Rights

© 1984 Kevin Wayne Whiting, All rights reserved.

Document Type

Thesis - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Expert systems (Computer science)
Database management
Data mining

Thesis Number

T 5116

Print OCLC #

11299387

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu:80/record=b2693333~S5

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