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

This book was born from a radical idea about artificial intelligence (AI) that unexpectedly
grew to be about much more. At first I was thinking only about AI algorithms, programs of …

Low population diversity is recognized as a factor in premature convergence of evolutionary
algorithms. We investigate program synthesis performance via grammatical evolution. We …

Evolutionary algorithms are a frequently used technique for designing morphology and
controller of a robot. However, a significant challenge for evolutionary algorithms is …

Abstract The Ant Trail problem has been widely investigated as a benchmark for automatic
design of algorithms. One must design the program of a virtual ant to collect all pieces of …

Novelty Search (NS) is a unique approach towards search and optimization, where an
explicit objective function is replaced by a measure of solution novelty. However, NS has …

Grammatical Evolution is an evolutionary algorithm that can evolve complete programs
using a Backus Naur form grammar as a plug-in component to describe the output …

This research builds on the hypothesis that the use of different fitness measures on the
different generations of genetic programming (GP) is more effective than the convention of …

Recent research on evolutionary algorithms has begun to focus on the issue of
generalization. While most works emphasize the evolution of high quality solutions for …

Over recent years, evolutionary computation research has begun to emphasize the issue of
generalization. Instead of evolving solutions that are optimized for a particular problem …