Within this book chapter we summarize Learning Classifier Systems (LCSs), a family of rule-
based learning systems with a more than forty-year-long research history, and differentiate …

The world around us is changing very fast mainly because of spectacular progress in
information and communication technologies. A phenomenon known only from science …

Depression, a prevalent mental health disorder, presents significant challenges in timely
diagnosis and intervention, emphasizing the importance of early detection for effective …

Data analytics plays a significant role within the context of the digital business landscape,
particularly concerning online sales, aiming to enhance understanding of customer …

Decision tree induction algorithms represent one of the most popular techniques for dealing
with classification problems. However, traditional decision-tree induction algorithms …

Multi-population genetic algorithms have been used with success for several multi-objective
optimization problems. In this paper, we present a new general multi-population genetic …

An evolutionary methods for an induction-based decision trees made a wide step
development in machine learning field. In this context, the majority of researches recently …

Adaptive boosting (AdaBoost) is a method for building classification ensemble, which
combines multiple classifiers built in an iterative process of reweighting instances. This …

Decision trees is a machine learning technique that searches the predictor space for the
variable and observed value that leads to the best prediction when the data are split into two …

Problem-solving strategies have been investigated in various informatics education
contexts. However, no substantial research has yet been conducted on the problem-solving …