If complexity is your problem, learning classifier systems (LCSs) may offer a solution. These
rule‐based, multifaceted, machine learning algorithms originated and have evolved in the …

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 …

Broadly conceived as computational models of cognition and tools for modeling complex
adaptive systems, later extended for use in adaptive robotics, and today also applied to …

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

Sentiment analysis of public views and spam detection from social media text messages are
two challenging data analysis tasks due to short informal text. This paper investigates the …

Learning classifier systems are leading evolutionary machine learning systems that employ
genetic algorithms to search for a set of optimally general and correct classification rules for …

An important strength of learning classifier systems (LCSs) lies in the combination of genetic
optimization techniques with gradient-based approximation techniques. The chosen …

The XCS classifier system has recently shown a high degree of competence on a variety of
data mining problems, but to what kind of problems XCS is well and poorly suited is seldom …

Urban road networks are an infrastructural key factor for modern cities. To facilitate an
efficient transportation of people and goods, it is crucial to optimise the networks' …

Evolutionary learning techniques are comparable in accuracy with other learning methods
such as Bayesian Learning, SVM, etc. These techniques often produce more interpretable …