A variety of methods have been applied to the architectural configuration and learning or
training of artificial deep neural networks (DNN). These methods play a crucial role in the …

Evolution provides a creative fount of complex and subtle adaptations that often surprise the
scientists who discover them. However, the creativity of evolution is not limited to the natural …

Neutral genetic drift is an evolutionary mechanism which can strongly aid the escape from
local optima. This makes neutral genetic drift an increasingly important property of …

Heritable phenotypic variation plays a central role in evolution by conferring rapid adaptive
capacity to populations. Mechanisms that can explain genetic diversity by describing …

Modularity is a desirable property for embodied agents, as it could foster their suitability to
different domains by disassembling them into transferable modules that can be reassembled …

A map** is local if it preserves neighbourhood. In Evolutionary Computation, locality is
generally described as the property that neighbouring genotypes correspond to …

Abstract Semantics has become a key topic of research in Genetic Programming (GP).
Semantics refers to the outputs (behaviour) of a GP individual when this is run on a dataset …

The facility layout problem is one of the fundamental production system management
problems. It has a significant impact on overall system efficiency. This paper introduces a …

Grammatical evolution (GE) is one of the most widespread techniques in evolutionary
computation. Genotypes in GE are bit strings while phenotypes are strings, of a language …

Redundancy is a ubiquitous feature of genetic programming (GP), with many-to-one
map**s commonly observed between genotype and phenotype, and between phenotype …