Abstract Random Boolean networks (RBNs) are models of genetic regulatory networks. It is
useful to describe RBNs as self-organizing systems to study how changes in the nodes and …

A definition of complexity based on logic functions, which are widely used as compact
descriptions of rules in diverse fields of contemporary science was explored. Detailed …

Emergent cooperative relations in ecosystems are ill understood, but have the potential to
strongly improve evolutionary computing. On the other hand, eco-evolutionary computation …

Cellular automata (CA) are discrete dynamical systems with a prominent place in the history
and study of artificial life. Here, we focus on the density classification task (DCT) in which a 1 …

This article presents a brief history of the Evolving Cellular Automata (EvCA) project. In the
EvCA project, a genetic algorithm was used to evolve cellular automata to perform certain …

The density classification or density determination is one among other ongoing problems for
studying the abilities of cellular automata to avail themselves of emergent collective …

Canalization is a property of Boolean automata that characterizes the extent to which
subsets of inputs determine (canalize) the output. Here, we investigate the role of …

The Density Classification Task is a well known test problem for two-state discrete dynamical
systems. For many years researchers have used a variety of evolutionary computation …

Cellular Automata are important tools in the study of complex interactions and analysis of
emergent behaviour. They have the ability to generate highly complex behaviour starting …

We present a method to eliminate redundancy in the transition tables of Boolean automata:
schema redescription with two symbols. One symbol is used to capture redundancy of …