Learning Classifier Systems: International Workshops, IWLCS 2003-2005, Revised Selected Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence): 4399 - Brossura
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This book constitutes the thoroughly refereed joint post-proceedings of three consecutive International Workshops on Learning Classifier Systems that took place in Chicago, IL in July 2003, in Seattle, WA in June 2004, and in Washington, DC in June 2005. Topics in the 22 revised full papers range from theoretical analysis of mechanisms to practical consideration for successful application of such techniques to everyday datamining tasks.
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Contenuti
Knowledge Representation.- Analyzing Parameter Sensitivity and Classifier Representations for Real-Valued XCS.- Use of Learning Classifier System for Inferring Natural Language Grammar.- Backpropagation in Accuracy-Based Neural Learning Classifier Systems.- Binary Rule Encoding Schemes: A Study Using the Compact Classifier System.- Mechanisms.- Bloat Control and Generalization Pressure Using the Minimum Description Length Principle for a Pittsburgh Approach Learning Classifier System.- Post-processing Clustering to Decrease Variability in XCS Induced Rulesets.- LCSE: Learning Classifier System Ensemble for Incremental Medical Instances.- Effect of Pure Error-Based Fitness in XCS.- A Fuzzy System to Control Exploration Rate in XCS.- Counter Example for Q-Bucket-Brigade Under Prediction Problem.- An Experimental Comparison Between ATNoSFERES and ACS.- The Class Imbalance Problem in UCS Classifier System: A Preliminary Study.- Three Methods for Covering Missing Input Data in XCS.- New Directions.- A Hyper-Heuristic Framework with XCS: Learning to Create Novel Problem-Solving Algorithms Constructed from Simpler Algorithmic Ingredients.- Adaptive Value Function Approximations in Classifier Systems.- Three Architectures for Continuous Action.- A Formal Relationship Between Ant Colony Optimizers and Classifier Systems.- Detection of Sentinel Predictor-Class Associations with XCS: A Sensitivity Analysis.- Application-Oriented Research and Tools.- Data Mining in Learning Classifier Systems: Comparing XCS with GAssist.- Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule.- Using XCS to Describe Continuous-Valued Problem Spaces.- The EpiXCS Workbench: A Tool for Experimentation and Visualization.
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Learning Classifier Systems: International Workshops, IWLCS 2003-2005, Revised Selected Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)
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Learning Classifier Systems: International Workshops, IWLCS 2003-2005, Revised Selected Papers (Lecture Notes in Computer Science, 4399)
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Learning Classifier Systems: International Workshops, IWLCS 2003-2005, Revised Selected Papers (Lecture Notes in Computer Science, 4399)
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Learning Classifier Systems
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the thoroughly refereed joint post-proceedings of three consecutive International Workshops on Learning Classifier Systems that took place in Chicago, IL in July 2003, in Seattle, WA in June 2004, and in Washington, DC in June 2005. Topics in the 22 revised full papers range from theoretical analysis of mechanisms to practical consideration for successful application of such techniques to everyday datamining tasks. 364 pp. Englisch. Codice articolo 9783540712305
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the thoroughly refereed joint post-proceedings of three consecutive International Workshops on Learning Classifier Systems that took place in Chicago, IL in July 2003, in Seattle, WA in June 2004, and in Washington, DC in June 2005. Codice articolo 4899176
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Learning Classifier Systems
ISBN 10: 3540712305
ISBN 13: 9783540712305
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Taschenbuch. Condizione: Neu. Neuware -The work embodied in this volume was presented across three consecutive e- tions of the International Workshop on Learning Classi er Systems that took place in Chicago (2003), Seattle (2004), and Washington (2005). The Genetic and Evolutionary Computation Conference, the main ACM SIGEvo conference, hosted these three editions. The topics presented in this volume summarize the wide spectrum of interests of the Learning Classi er Systems (LCS) community. The topics range from theoretical analysis of mechanisms to practical cons- eration for successful application of such techniques to everyday data-mining tasks. When we started editing this volume, we faced the choice of organizing the contents in a purely chronologicalfashion or as a sequence of related topics that help walk the reader across the di erent areas. In the end we decided to or- nize the contents by area, breaking the time-line a little. This is not a simple endeavor as we can organize the material using multiple criteria. The tax- omy below is our humble e ort to provide a coherent grouping. Needless to say, some works may fall in more than one category. The four areas are as follows: Knowledge representation. These chapters elaborate on the knowledge r- resentations used in LCS. Knowledge representation is a key issue in any learning system and has implications for what it is possible to learn and what mechanisms shouldbe used. Four chapters analyze di erent knowledge representations and the LCS methods used to manipulate them.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 364 pp. Englisch. Codice articolo 9783540712305
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Learning Classifier Systems : International Workshops, IWLCS 2003-2005, Revised Selected Papers
Editore:
Springer Berlin Heidelberg, 2007
ISBN 10: 3540712305
ISBN 13: 9783540712305
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Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The work embodied in this volume was presented across three consecutive e- tions of the International Workshop on Learning Classi er Systems that took place in Chicago (2003), Seattle (2004), and Washington (2005). The Genetic and Evolutionary Computation Conference, the main ACM SIGEvo conference, hosted these three editions. The topics presented in this volume summarize the wide spectrum of interests of the Learning Classi er Systems (LCS) community. The topics range from theoretical analysis of mechanisms to practical cons- eration for successful application of such techniques to everyday data-mining tasks. When we started editing this volume, we faced the choice of organizing the contents in a purely chronologicalfashion or as a sequence of related topics that help walk the reader across the di erent areas. In the end we decided to or- nize the contents by area, breaking the time-line a little. This is not a simple endeavor as we can organize the material using multiple criteria. The tax- omy below is our humble e ort to provide a coherent grouping. Needless to say, some works may fall in more than one category. The four areas are as follows: Knowledge representation. These chapters elaborate on the knowledge r- resentations used in LCS. Knowledge representation is a key issue in any learning system and has implications for what it is possible to learn and what mechanisms shouldbe used. Four chapters analyze di erent knowledge representations and the LCS methods used to manipulate them. Codice articolo 9783540712305
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