Grammar formalisms are one of the key representation structures in Computer Science. So it
is not surprising that they have also become important as a method for formalizing …

Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of
this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In …

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 …

Dynamic environments abound and offer particular challenges for all optimisation and
problem solving methods. A well-known strategy for survival in dynamic environments is to …

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 …

Genetic programming approaches have been employed in the literature to automatically
design constructive heuristics for cutting and packing problems. These heuristics obtain …

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 …

Abstract This paper introduces Structured Grammatical Evolution, a new genotypic
representation for Grammatical Evolution, where each gene is explicitly linked to a non …

Grammatical Evolution (GE) has a long history in evolutionary computation. Central to the
behaviour of GE is the use of a linear representation and grammar to map individuals from …

This paper describes Christiansen grammar evolution (CGE), a new evolutionary automatic
programming algorithm that extends standard grammar evolution (GE) by replacing context …