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.
Recommended Citation
Whiting, Kevin W.; DeKock, Arlan R.; and Prater, John Bruce, "A Focus Of Attention Algorithm For Expert Systems" (1984). Computer Science Technical Reports. 55.
https://scholarsmine.mst.edu/comsci_techreports/55
Department(s)
Computer Science
Report Number
CSC-84-12
Document Type
Technical Report
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 1984 University of Missouri--Rolla, All rights reserved.
Publication Date
01 Jul 1984
Comments
This report is substantially the M.S. thesis of the first author, completed July, 1984.