Cartesian Genetic Programming (CGP) is a well-known form of Genetic Programming
developed by Julian Miller in 1999-2000. In its classic form, it uses a very simple integer …

Cartesian genetic programming, a well-established method of genetic programming, is
approximately 20 years old. It represents solutions to computational problems as graphs. Its …

Cartesian Genetic Programming (CGP) is a variant of Genetic Programming with several
advantages. During the last one and a half decades, CGP has been further extended to …

A fast learning neuroevolutionary algorithm for both feedforward and recurrent networks is
proposed. The method is inspired by the well known and highly effective Cartesian genetic …

Neuroevolution, the application of evolutionary algorithms to artificial neural networks
(ANNs), is well-established in machine learning. Cartesian Genetic Programming (CGP) is a …

A fast learning neuro-evolutionary technique that evolves Artificial Neural Networks using
Cartesian Genetic Programming (CGPANN) is used to detect the presence of breast cancer …

In this paper we compare systematically the most promising neuroevolutionary methods and
two new original methods on the double-pole balancing problem with respect to: the ability …

This chapter aims to give an overview of recent applications of Evolutionary Machine
Learning (EML) to control including opportunities and challenges. Control is at the heart of …

Use of cloud resources has increased with the increasing trend of organizations and
governments towards cloud adaptation. This increase in cloud resource usage, leads to …

A genetic programming (GP) algorithm is developed to estimate the minimum spouting
velocity (U ms) in the spouted beds with a cone base. In order to have a general model, five …