Research on potential interactions between connectionist learning systems, ie, artificial
neural networks (ANNs), and evolutionary search procedures, like genetic algorithms (GAs) …

We present a comprehensive review of the evolutionary design of neural network
architectures. This work is motivated by the fact that the success of an Artificial Neural …

Swarm intelligence refers to a kind of problem-solving ability that emerges in the interactions
of simple information-processing units. The concept of a swarm suggests multiplicity …

Learning and evolution are two fundamental forms of adaptation. There has been a great
interest in combining learning and evolution with artificial neural networks (ANNs) in recent …

Evolutionary Robotics is a method for automatically generating artificial brains and
morphologies of autonomous robots. This approach is useful both for investigating the …

Genetic algorithms are a robust adaptive optimization method based on biological
principles. A population of strings representing possible problem solutions is maintained …

This paper presents a new evolutionary system, ie, EPNet, for evolving artificial neural
networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's …

A comprehensive introduction to new approaches in artificial intelligence and robotics that
are inspired by self-organizing biological processes and structures. New approaches to …

Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

Computational Intelligence: Concepts to Implementations provides the most complete and
practical coverage of computational intelligence tools and techniques to date. This book …