Zusammenfassung
The issue of deletion schemes for classifier systems
has received little attention. In a standard genetic
algorithm a chromosome can be evaluated (assigned a
reasonable fitness) immediately. In classifier systems,
however, a chromosome can only be fully evaluated after
many interactions with the environment, since a
chromosome may generalize over many environmental
states. A new technique which protects poorly evaluated
chromosomes outperforms both techniques from (Wilson,
1995) in two very different single step problems.
Results indicate the XCS classifier system is able to
learn single step problems for which no (or few) useful
generalizations can be made over the input string,
despite its drive towards accurate generalization.
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