What should a classifier system learn?

被引：0
|
作者：
Kovacs, T [1 ]
机构：
[1] Univ Birmingham, Sch Comp Sci, Birmingham B15 2TT, W Midlands, England
来源：
PROCEEDINGS OF THE 2001 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2001年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We consider the issue of how a classifier system should learn to represent a Boolean function. We identify four properties which may be desirable of a representation; that it be complete, accurate, minimal and nonoverlapping, and distinguish variations on two of these properties for the XCS system. We question whether the bias against overlapping rules evident in some systems is appropriate, and find that XCS's bias against overlapping rules is very strong.
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页码：775 / 782
页数：8
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