Download Ebook BookLearning Classifier Systems 5th International Workshop IWLCS 2002 Granada Spain September 7-8 2002 Revised Papers (Lecture Notes in Computer Science)

Free Download Learning Classifier Systems 5th International Workshop IWLCS 2002 Granada Spain September 7-8 2002 Revised Papers (Lecture Notes in Computer Science)



Free Download Learning Classifier Systems 5th International Workshop IWLCS 2002 Granada Spain September 7-8 2002 Revised Papers (Lecture Notes in Computer Science)

Free Download Learning Classifier Systems 5th International Workshop IWLCS 2002 Granada Spain September 7-8 2002 Revised Papers (Lecture Notes in Computer Science)

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Published on: 2009-02-22
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Original language: English
Free Download Learning Classifier Systems 5th International Workshop IWLCS 2002 Granada Spain September 7-8 2002 Revised Papers (Lecture Notes in Computer Science)

The 5th International Workshop on Learning Classier 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 classier system, iLCS, and tests it on the Wisconsin Breast Cancer classication problem. Dixon et al. present an algorithm for reducing the solutions evolved by the classier system XCS, so as to produce a small set of readily understandable rules. Enee and Barbaroux take a close look at Pittsburgh-style classier 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 classication performance of learning classier systems. The two papers by Kovacs deal with an important theoretical issue in learning classier 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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