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Learning Classifier Systems - 5th International Workshop, IWLCS 2002, Granada, Spain, September 7-8, 2002, Revised Papers (Paperback, 2003 ed.)
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Learning Classifier Systems - 5th International Workshop, IWLCS 2002, Granada, Spain, September 7-8, 2002, Revised Papers (Paperback, 2003 ed.)
Series: Lecture Notes in Computer Science, 2661
Expected to ship within 10 - 15 working days
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The 5th International Workshop on Learning Classi?er Systems
(IWLCS2002) was held September 7-8, 2002, in Granada, Spain, during
the 7th International Conference on Parallel Problem Solving from
Nature (PPSN VII). We have included in this volume revised and
extended versions of the papers presented at the workshop. In the
?rst paper, Browne introduces a new model of learning classi?er
system, iLCS, and tests it on the Wisconsin Breast Cancer
classi?cation problem. Dixon et al. present an algorithm for
reducing the solutions evolved by the classi?er system XCS, so as
to produce a small set of readily understandable rules. Enee and
Barbaroux take a close look at Pittsburgh-style classi?er systems,
focusing on the multi-agent problem known as El-farol. Holmes and
Bilker investigate the effect that various types of missing data
have on the classi?cation performance of learning classi?er
systems. The two papers by Kovacs deal with an important
theoretical issue in learning classi?er systems: the use of
accuracy-based ?tness as opposed to the more traditional
strength-based ?tness. In the ?rst paper, Kovacs introduces a
strength-based version of XCS, called SB-XCS. The original XCS and
the new SB-XCS are compared in the second paper, where - vacs
discusses the different classes of solutions that XCS and SB-XCS
tend to evolve.
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