This is the second edition of our 2003 book. It is primarily a book for lecturers and graduate
and undergraduate students. To this group the book offers a thorough introduction to …

This e-book is devoted to global optimization algorithms, which are methods to find optimal
solutions for given problems. It especially focuses on Evolutionary Computation by …

Rule-based evolutionary online learning systems, often referred to as Michiganstyle learning
classifier systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland …

Learning classifier systems (LCSs) are rule-based systems that automatically build their
ruleset. At the origin of Holland's work, LCSs were seen as a model of the emergence of …

Abstract [Learning] Classifier systems are a kind of rule-based system with general
mechanisms for processing rules in parallel, for adaptive generation of new rules, and for …

The evolutionary learning mechanism in XCS strongly depends on its accuracy-based
fitness approach. The approach is meant to result in an evolutionary drive from classifiers of …

Classifier systems are an intriguing approach to a broad range of machine learning
problems, based on automated generation and evaluation of condi tion/action rules …

The accuracy-based XCS classifier system has been shown to solve typical data mining
problems in a machine-learning competitive way. However, successful applications in …

Many learning classifier system (LCS) implementations are restricted to the binary problem
realm. Recently, the XCS classifier system was enhanced to be able to handle real-valued …

Medical data exhibit certain features that make their classification stand out as a distinct field
of research. Several medical classification tasks exist, among which medical diagnosis and …