Abstract
LCSs as a concept and framework are suited to a wide range of applications. This chapter describes how the various LCS methods can be chosen and adapted for certain types of problems, such as data mining or robot control. Specifically, this chapter offers a basic setup guide discussing logistics, design considerations, setting run parameters, tuning for performance, and troubleshooting. This book concludes with a summary of useful LCS resources beyond this introductory textbook.
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Urbanowicz, R.J., Browne, W.N. (2017). Applying LCSs. In: Introduction to Learning Classifier Systems. SpringerBriefs in Intelligent Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-55007-6_5
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DOI: https://doi.org/10.1007/978-3-662-55007-6_5
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Publisher Name: Springer, Berlin, Heidelberg
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