Explainable artificial intelligence (XAI) has received great interest in the recent decade, due
to its importance in critical application domains, such as self-driving cars, law, and …

One of the long-term goals in evolutionary robotics is to be able to automatically synthesize
controllers for real autonomous robots based only on a task specification. While a number of …

While evolutionary computation and evolutionary robotics take inspiration from nature, they
have long focused mainly on problems of performance optimization. Yet evolution in nature …

Novelty search is a state-of-the-art evolutionary approach that promotes behavioural novelty
instead of pursuing a static objective. Along with a large number of successful applications …

Novelty search is a tool in evolutionary and swarm robotics for maintaining the diversity of
population needed for continuous robotic operation. It enables nature-inspired algorithms to …

The particle swarm optimization algorithm is primarily inspired by the natural behaviour of
swarms and achieves important results in different applications. However, it is not exempt …

Research on semantics in Genetic Programming (GP) has increased over the last number of
years. Results in this area clearly indicate that its use in GP considerably increases …

Genetic Improvement (GI) focuses on the development of evolutionary methods to automate
software engineering tasks, such as performance improvement or software bugs removal …

Clustering is a difficult and widely studied data mining task, with many varieties of clustering
algorithms proposed in the literature. Nearly all algorithms use a similarity measure such as …

Cooperative coevolutionary algorithms (CCEAs) rely on multiple coevolving populations for
the evolution of solutions composed of coadapted components. CCEAs enable, for instance …