Artificial immune systems (AIS) can be defined as computational systems inspired by
theoretical immunology, observed immune functions, principles and mechanisms in order to …

In this thesis the class of generative representations is defined and it is shown that this class
of representations improves the scalability of evolutionary design systems by automatically …

The back-propagation (BP) neural network and the radial basis function (RBF) neural
network have been widely used in many engineering applications. In general, the BP neural …

There exist many ideas and assumptions about the development and meaning of modularity
in biological and technical neural systems. We empirically study the evolution of …

This paper describes the application of two evolutionary algorithms to the feedforward
neural networks used in classification problems. Besides of a simple backpropagation …

The paper describes a methodology for constructing transfer functions for the hidden layer of
a back-propagation network, which is based on evolutionary programming. The method …

This paper describes the simulation of two hybrid evolutionary algorithms (EAs) to the
feedforward neural networks (NNs) used in classification problems. Besides …

In this paper we describe the genetic programming system GGP operating on graphs and
introduce the notion of graph isomorphisms to explain how they influence the dynamics of …

Abstract An Evolutionary Algorithm is used to optimize the architecture and activation
functions of an Artificial Neural Networks (ANN). It will be shown that it is possible, with the …

Concepts from graph theory and molecular evolution are proposed for analyzing the
redundancy in the genotype-phenotype mapping in structure optimization stemming from …