Computers thatprogram themselves' has long been an aim of computer scientists. Recently
genetic programming (GP) has started to show its promise by automatically evolving …

Abstract This chapter describes Grammatical Evolution (GE) in detail (Ryan et al., 1998;
O'Neill and Ryan, 2001; O'Neill, 2001). We show that it is an evolutionary algorithm (EA) that …

The majority of current genetic algorithms (GAs), while inspired by natural evolutionary
systems, are seldom viewed as biologically plausible models. This is not a criticism of GAs …

The problem of evolving, using mutation, an artificial ant to follow the Santa Fe trail is used to
study the well known genetic programming feature of growth in solution length. Known …

This article compares the traditional, fixed problem representation style of a genetic
algorithm (GA) with a new floating representation in which the building blocks of a problem …

Abstract Design patterns capture the essentials of recurring best practice in an abstract form.
Their merits are well established in domains as diverse as architecture and software …

A brief survey of biological research on non-coding DNA is presented here. There has been
growing interest in the effects of non-coding segments in evolutionary algorithms (EAs). To …

We describe an investigation into the design of different grammars on Grammatical
Evolution. As part of this investigation we introduce introns using the grammar as a …

Modern optimization approaches have attracted an increasing number of scientists, decision
makers, and researchers. As new issues in this field emerge, different optimization …

Coding segments are those subsegments of the chromosome that contribute positively to the
fitness evaluation of the chromosome. Clique detection is a NP-complete problem in which …