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Applying Multiple Classification Ripple Round Rules to a Complex Configuration Task

Citation

Bindoff, I and Kang, BH, Applying Multiple Classification Ripple Round Rules to a Complex Configuration Task, Lecture Notes in Artificial Intelligence - Proceedings of AI 2011: Advances in Artificial Intelligence, 5-8 December 2011, Perth, Australia, pp. 481-490. ISBN 978-3-642-25832-9 (2011) [Refereed Conference Paper]

Copyright Statement

Copyright 2011 Springer-Verlag

DOI: doi:10.1007/978-3-642-25832-9

Abstract

A new expert systems methodology was developed, building on existing work on the Ripple Down Rules (RDR) method. RDR methods offer a solution to the maintenance problem which has otherwise plagued traditional rule- based expert systems. However, they are, in their classic form, unable to support rules which use existing classifications in their rule conditions. The new method outlined in this paper is suited to multiple classification tasks, and maintains all the significant advantages of previous RDR offerings, while also allowing the creation of rules which use classifications in their conditions. It improves on previous offerings in this field by having fewer restrictions regarding where and how these rules may be used. The method has undergone initial testing on a complex configuration task, which would be practically unsolvable with traditional multiple classification RDR methods, and has performed well, reaching an accuracy in the 90th percentile after being trained with 1073 rules over the course of classifying 1000 cases, taking ~12 expert hours.

Item Details

Item Type:Refereed Conference Paper
Keywords:ripple, down, rules, multiple, classification, round, configuration, knowledge acquisition.
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Artificial Intelligence and Image Processing not elsewhere classified
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Computer Software and Services not elsewhere classified
Author:Bindoff, I (Dr Ivan Bindoff)
Author:Kang, BH (Professor Byeong Kang)
ID Code:76176
Year Published:2011
Deposited By:Computing and Information Systems
Deposited On:2012-03-01
Last Modified:2017-11-20
Downloads:0

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