Cartesian genetic programming encoded artificial neural networks: a comparison using three benchmarks

By Andrew James Turner, Julian Francis Miller. 2013

53 citations recorded by the source corpus.

Subfields: Artificial Intelligence

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jörg Stork
2. Martin Zaefferer
3. Thomas Bartz-Beielstein
4. Andrew James Turner
5. Julian Francis Miller
6. Frank Hutter
7. Gul Muhammad Khan
8. Holger H. Hoos

Citations in the corpus

• Introducing a cross platform open source Cartesian Genetic Programming library (2014, methodology): “NeuroEvolution is a recent application of CGP termed Cartesian Genetic Programming of Artificial Neural Networks (CGPANN) [5] [16].”
• Distance-based Kernels for Surrogate Model-based Neuroevolution (2018, background): “SMBO with phenotypic distance kernels, which are based on generated outputs of each ANN, shows significantly better results than with genotypic distances or basic CGPANN.”
• Cartesian Genetic Programming (2015, background): “In a later chapter, ways of developing art using CGP will be considered in detail.”