Introduction to Learning Classifier Systems

Ryan J. Urbanowicz|Will N. Browne

ISBN 10: 3662550067 / ISBN 13: 9783662550069

Published by Springer Berlin Heidelberg, 2017

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.

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Bibliographic Details

• Title: Introduction to Learning Classifier Systems
• Publisher: Springer Berlin Heidelberg
• Publication Date: 2017
• Language: English
• ISBN 10: 3662550067
• ISBN 13: 9783662550069
• Binding: Soft cover
• Condition: New

About this title

Synopsis

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

About the Author

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.