In this paper, we develop techniques based on evolvability statistics of the fitness land-
scape surrounding sampled solutions. Averaging the measures over a sample of equal …

'Evolvability'–the ability to undergo adaptive evolution–is a key concept for understanding
and predicting the response of biological systems to environmental change. Evolvability has …

2 Representations for Genetic and Evolutionary Algorithms Page 1 2 Representations for Genetic
and Evolutionary Algorithms In this second chapter, we present an introduction into the field of …

The graph-based Cartesian genetic programming system has an unusual genotype
representation with a number of advantageous properties. It has a form of redundancy …

This paper discusses how the use of redundant representations influences the performance
of genetic and evolutionary algorithms. Representations are redundant if the number of …

Evolutionary algorithms apply the process of variation, reproduction, and selection to look for
an individual capable of solving the task at hand. In order to improve the evolvability of a …

Evolution has not typically been recognised by linguists as a constraining factor when
developing linguistic theories. This book demonstrates that our theories of language must …

In biological systems, individual phenotypes are typically adopted by multiple genotypes.
Examples include protein structure phenotypes, where each structure can be adopted by a …

We propose building neutral networks in needle-in-haystack fitness landscapes to assist an
evolutionary algorithm to perform search. The experimental results on four different …

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 …