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Learning Classifier Systems : 5th International Workshop, IWLCS 2002, Granada, Spain, September 7-8, 2002, Revised Papers - Pier Luca Lanzi

Learning Classifier Systems

5th International Workshop, IWLCS 2002, Granada, Spain, September 7-8, 2002, Revised Papers

By: Pier Luca Lanzi (Editor), Wolfgang Stolzmann (Editor), Stewart W. Wilson (Editor)

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Published: 24th November 2003
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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.

Balancing Specificity and Generality in a Panmictic-Based Rule-Discovery Learning Classifier Systemp. 1
A Ruleset Reduction Algorithm for the XCS Learning Classifier Systemp. 20
Adapted Pittsburgh-Style Classifier-System: Case-Studyp. 30
The Effect of Missing Data on Learning Classifier System Learning Rate and Classification Performancep. 46
XCS's Strength-Based Twin: Part Ip. 61
XCS's Strength-Based Twin: Part IIp. 81
Further Comparison between ATNoSFERES and XCSMp. 99
Accuracy, Parsimony, and Generality in Evolutionary Learning Systems via Multiobjective Selectionp. 118
Anticipatory Classifier System Using Behavioral Sequences in Non-Markov Environmentsp. 143
Mapping Artificial Immune Systems into Learned Classifier Systemsp. 163
The 2003 Learning Classifier Systems Bibliographyp. 187
Author Indexp. 231
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9783540205449
ISBN-10: 3540205446
Series: Lecture Notes in Artificial Intelligence
Audience: Tertiary; University or College
Format: Paperback
Language: English
Number Of Pages: 233
Published: 24th November 2003
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 23.3 x 15.5  x 1.3
Weight (kg): 0.77