The main focus of this paper is on the family of evolutionary algorithms and their real-life
applications. We present the following algorithms: genetic algorithms, genetic programming …

Artificial intelligence (AI) emphasises the creation of intelligent machines/systems that
function like humans. AI has been applied to many real-world applications. Machine …

Discovering the underlying mathematical expressions describing a dataset is a core
challenge for artificial intelligence. This is the problem of $\textit {symbolic regression} …

In this paper we provide a broad benchmarking of recent genetic programming approaches
to symbolic regression in the context of state of the art machine learning approaches. We …

Genetic programming (GP) is a powerful evolutionary algorithm that has been widely used
for solving many real-world optimization problems. However, traditional GP can only solve a …

Lexicase selection is a parent selection method that considers test cases separately, rather
than in aggregate, when performing parent selection. It performs well in discrete error …

Several methods to incorporate semantic awareness in genetic programming have been
proposed in the last few years. These methods cover fundamental parts of the evolutionary …

Abstract The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) is a model-based
EA framework that has been shown to perform well in several domains, including Genetic …

Energy consumption has long been emphasized as an important policy issue in today's
economies. In particular, the energy efficiency of residential buildings is considered a top …

The field of natural computing has been the focus of a substantial research effort in recent
decades. One particular strand of this concerns the development of computational …