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Summary: Rule Evolution in Order based Diagnostic Systems
Robert I. Graham and Tughrul Arslan
Department of Electronics and Electrical Engineering
The University of Edinburgh
King's Buildings
Mayfield Rd
Edinburgh EH9 3JL
(Int i44) I31 650 5619
Robert.Graham@ee.ed.ac.uk
Abstract
The authors present a novel system designed to evolve
sets of rule bases used to optimise the order of lists of
data arrays. Based upon induction learning techniques,
an ulgorithm is described which is able to learn the rules
most appropriate to ordering data in an attempt to
promote a particular trait. A classifier system is
employed as the main sorting engine, with a genetic
ulgorithm in place to evolve newer, more proficient rules.
As a test-bench for the sorting technique, the algorithm
was trained to optimise lists of suspect components
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