This cluster of papers focuses on the application of genetic programming in machine learning, particularly in the areas of classification, feature selection, symbolic regression, and evolvable hardware. It explores the use of evolutionary algorithms and learning classifier systems to solve complex problems, with an emphasis on multiobjective optimization and semantic genetic programming.