This book provides a comprehensive introduction to the design and analysis of Learning Classifier Systems (LCS) from the perspective of machine learning. Systematic follow this approach, is to show how generic machine learning methods can be applied to design LCS algorithms from first principles of their underlying probabilistic model, which in this book? This approach is holistic in the sense that the uniform design metaphor-driven objectives essentially covers all aspects of the LCS and put them on a solid foundation, in addition to allowing the transfer of the theoretical foundation of machine used various methods of learning to the LCS.