Abstract Learning Classifier Systems (LCSs) are a group of rule-based evolutionary
computation techniques, which have been frequently applied to data mining tasks. The …

The International Workshop on Learning Classifier Systems (IWLCS) is an annual workshop
at the GECCO conference where new concepts and results regarding learning classifier …

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 verification of a new product is of major importance for companies. With the rise of test
automation, companies start to rely on huge numbers of tests. Often, it is not feasible to run …

Testing is a crucial part in the development of new products. With the rise of test automation
methods, companies start relying on an even higher number of tests. Sometimes it is not …

In the field of rule-based approaches to Machine Learning, the XCS classifier system (XCS)
is a well-known representative of the learning classifier systems family. By using a genetic …

Interest in reinforcement learning (RL) has recently surged due to the application of deep
learning techniques, but these connectionist approaches are opaque compared with …

Self-adaptation is crucial for cyber-physical systems (CPS) to meet their requirements in
environments characterized by complexity and uncertainty. As many situations that CPS …

With the rise of test automation, companies start to rely on large amounts of test cases.
However, there are situations where it is unfeasible to perform every test case as only a …

❖ Interpretability by design• Knowledge represented by IF-THEN rules• Allows for explicit
injection of expert knowledge❖ Complexity reduction by design❖ Online adaptivity to …