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 …

Michigan-style learning classifier systems (M-LCSs) represent an adaptive and powerful
class of evolutionary algorithms which distribute the learned solution over a sizable …

During the last decade, research on Genetic-Based Machine Learning has resulted in
several proposals of supervised learning methodologies that use evolutionary algorithms to …

There is an underlying assumption on most model building processes: given a learned
classifier, it should be usable to explain unseen data from the same given problem. Despite …

I entered the world of Learning Classifier Systems (LCS) through their introduction by Will
Browne as part of a lecture series on “Advanced Artificial Intelligence” at the University of …

Hyperspectral photothermal mid-infrared spectroscopic imaging (HP-MIRSI) is an emerging
technology with promising applications in cervical cancer diagnosis and quantitative, label …

In each year there are thousands of people die due to prostate cancer. Near-infrared (NIRF)
optical imaging is a new technique that uses the high absorption of hemoglobin in prostate's …

Over the recent years, research on Learning Classifier Systems (LCSs) got more and more
pronounced and diverse. There have been significant advances of the LCS field on various …