Introduction to Learning Classifier Systems 2017 Edition Contributor(s): Urbanowicz, Ryan J. (Author), Browne, Will N. (Author) |
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ISBN: 3662550067 ISBN-13: 9783662550069 Publisher: Springer OUR PRICE: $56.99 Product Type: Paperback Published: September 2017 |
Additional Information |
BISAC Categories: - Computers | Intelligence (ai) & Semantics - Computers | Computer Science - Mathematics | Applied |
Dewey: 006.3 |
Series: Springerbriefs in Intelligent Systems |
Physical Information: 0.3" H x 6.14" W x 9.21" (0.45 lbs) 123 pages |
Descriptions, Reviews, Etc. |
Publisher Description: This accessible introduction shows the reader how to understand, implement, adapt, and apply Learning Classifier Systems (LCSs) to interesting and difficult problems. The text builds an understanding from basic ideas and concepts. The authors first explore learning through environment interaction, and then walk through the components of LCS that form this rule-based evolutionary algorithm. The applicability and adaptability of these methods is highlighted by providing descriptions of common methodological alternatives for different components that are suited to different types of problems from data mining to autonomous robotics.
The authors have also paired exercises and a simple educational LCS (eLCS) algorithm (implemented in Python) with this book. It is suitable for courses or self-study by advanced undergraduate and postgraduate students in subjects such as Computer Science, Engineering, Bioinformatics, and Cybernetics, and by researchers, data analysts, and machine learning practitioners. |