Advances in Learning Classifier Systems (Paperback)

Pier L. Lanzi

ISBN 10: 3540437932 / ISBN 13: 9783540437932

Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2002

About this Item

Paperback. This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001, held in San Francisco, CA, USA, in July 2001. The 12 revised full papers presented together with a special paper on a formal description of ACS have gone through two rounds of reviewing and improvement. The first part of the book is devoted to theoretical issues of learning classifier systems including the influence of exploration strategy, self-adaptive classifier systems, and the use of classifier systems for social simulation. The second part is devoted to applications in various fields such as data mining, stock trading, and power distributionn networks. These are the refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001. The first part is devoted to theoretical issues, and the second to applications in various fields such as data mining, stock trading, and power distribution networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783540437932

Bibliographic Details

• Title: Advances in Learning Classifier Systems (Paperback)
• Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin
• Publication Date: 2002
• Language: English
• ISBN 10: 3540437932
• ISBN 13: 9783540437932
• Binding: Paperback
• Condition: new

About this title

Synopsis

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Learning Classifier Systems, IWLCS 2001, held in San Francisco, CA, USA, in July 2001.
The 12 revised full papers presented together with a special paper on a formal description of ACS have gone through two rounds of reviewing and improvement. The first part of the book is devoted to theoretical issues of learning classifier systems including the influence of exploration strategy, self-adaptive classifier systems, and the use of classifier systems for social simulation. The second part is devoted to applications in various fields such as data mining, stock trading, and power distributionn networks.