Abstract Automatic Machine Learning is a growing area of machine learning that has a
similar objective to the area of hyper-heuristics: to automatically recommend optimized …

Grammars have attracted the attention of researchers within the Evolutionary Computation
field, specially from the Genetic Programming community. The most successful example of …

Structured grammatical evolution (SGE) is a new genotypic representation for grammatical
evolution (GE). It comprises a hierarchical organization of the genes, where each locus is …

A frequently overlooked consideration when using Grammatical Evolution (GE) is grammar
design. This is because there is an infinite number of grammars that can specify the same …

Grammatical Evolution (GE) is one of the most popular Genetic Programming (GP) variants,
and it has been used with success in several problem domains. Since the original proposal …

Grammatical evolution is one of the most used variants of genetic programming, and ever
since its introduction, several improvements have been suggested. One of these concerns …

Genetic Programming (GP) is an heuristic method that can be applied to many Machine
Learning, Optimization and Engineering problems. In particular, it has been widely used in …

Abstract This work proposes Adaptive Facilitated Mutation, a self-adaptive mutation method
for Structured Grammatical Evolution (SGE), biologically inspired by the theory of facilitated …

We introduce a new cybersecurity project named RIVALS. RIVALS will assist in developing
network defense strategies through modeling adversarial network attack and defense …

Grammars are useful formalisms to specify constraints, and not surprisingly, they have
attracted the attention of Evolutionary Computation (EC) researchers to enforce problem …