Evolutionary algorithms have been used to solve a number of variable-length problems,
many of which share a common representation. A set of design variables is repeatedly …

Cellular Automata (CA) are a remarkable example of morphogenetic system, where cells
grow and self-organize through local interactions. CA have been used as abstractions of …

This chapter outlines the general approaches being used by computational biologists to
simulate evolution, and reviews some of the major impacts this work is having on biological …

The genomes of biological organisms are not fixed in size. They evolved and diverged into
different species acquiring new genes and thus having different lengths. In a way, biological …

A novel method for regulation of gene expression for artificial cellular systems is introduced.
It is based on an instructon-based representation which allows self-modification of genotype …

Genetic Regulatory Networks (GRNs) implementations have a high degree of variability in
their details. Parameters, encoding methods, and dynamics formulas all differ in the …

Optimization problems traditionally involve fixed-length representations to specify a
description of a solution. Every solution defines the same number of design variables …

The importance of individual cells in a developing multicellular organism is well known, but
precisely how the individual cellular characteristics of those cells collectively drive the …

The importance of individual cells in a developing multicellular organism is well known but
precisely how the individual cellular characteristics of those cells collectively drive the …

Medicine is an important and challenging area for machine learning and computational
intelligence approaches. Evolutionary algorithms, in particular, offer a number of advantages …