SpringerBriefs in Intelligent Systems

Introduction to Learning Classifier Systems

Authors: Urbanowicz, Ryan J., Browne, Will N.

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  • Learning Classifier Systems (LCSs) are a powerful and well-established rule-based machine learning technique but they have yet to be widely adopted due to a steep learning curve, their rich nature, and a lack of resources, and this is the first accessible introduction
  • Authors gave related tutorial at key international conference over multiple years
  • Suitable for undergraduate and postgraduate students, data analysts, and machine learning practitioners
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eBook 41,64 €
price for Spain (gross)
  • ISBN 978-3-662-55007-6
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 51,99 €
price for Spain (gross)
  • ISBN 978-3-662-55006-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

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.

About the authors

Ryan Urbanowicz is a postdoctoral research associate in the Dept. of Biostatistics, Epidemiology, and Informatics in the Perelman School of Medicine at the University of Pennsylvania. He received his PhD in Genetics from Dartmouth College, and a B.S. and M.Eng. in Biological Engineering from Cornell University. His areas of research include bioinformatics, data mining, machine learning, evolutionary algorithms, learning classifier systems, data visualization, and epidemiology. He has cochaired the Intl. Workshop on Learning Classifier Systems and presented LCS tutorials at GECCO.

Will Browne is an Associate Professor in the School of Engineering and Computer Science of Victoria University of Wellington. He received his Eng.D. from Cardiff University. His main area of research is applied cognitive systems, in particular cognitive robotics, Learning Classifier Systems (LCSs), and modern heuristics for industrial application. He has cochaired the Intl. Workshop on Learning Classifier Systems, and chaired the Genetics-Based Machine Learning track and copresented the LCS tutorial at GECCO.

Reviews

“Introduction to Learning Classifier Systems is an excellent textbook and introduction to Learning Classifier Systems. … The book is completed with Python code available through a link included in the book. … Urbanowicz and Browne recommend their book for undergraduate and postgraduate students, data analysts, and machine learning practitioners alike.” (Analía Amandi, Genetic Programming and Evolvable Machines, Vol. 19 (4), December, 2018)

Table of contents (5 chapters)

Buy this book

eBook 41,64 €
price for Spain (gross)
  • ISBN 978-3-662-55007-6
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 51,99 €
price for Spain (gross)
  • ISBN 978-3-662-55006-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Introduction to Learning Classifier Systems
Authors
Series Title
SpringerBriefs in Intelligent Systems
Copyright
2017
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
The Author(s)
eBook ISBN
978-3-662-55007-6
DOI
10.1007/978-3-662-55007-6
Softcover ISBN
978-3-662-55006-9
Series ISSN
2196-548X
Edition Number
1
Number of Pages
XIII, 123
Number of Illustrations
23 b/w illustrations, 4 illustrations in colour
Topics