Cartesian genetic programming

J Miller, A Turner - Proceedings of the Companion Publication of the …, 2015 - dl.acm.org
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 …

Genetic programming needs better benchmarks

J McDermott, DR White, S Luke, L Manzoni… - Proceedings of the 14th …, 2012 - dl.acm.org
Genetic programming (GP) is not a field noted for the rigor of its benchmarking. Some of its
benchmark problems are popular purely through historical contingency, and they can be …

Cartesian genetic programming: its status and future

JF Miller - Genetic Programming and Evolvable Machines, 2020 - Springer
Cartesian genetic programming, a well-established method of genetic programming, is
approximately 20 years old. It represents solutions to computational problems as graphs. Its …

Recent developments in cartesian genetic programming and its variants

A Manazir, K Raza - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
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 …

Fast learning neural networks using cartesian genetic programming

MM Khan, AM Ahmad, GM Khan, JF Miller - Neurocomputing, 2013 - Elsevier
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 …

Evolutionary Machine Learning in Medicine

MA Lones, SL Smith - Handbook of Evolutionary Machine Learning, 2023 - Springer
This chapter reviews applications of evolutionary machine learning within the medical
domain. It is divided into three parts. The first two parts give examples of recent work in two …

The delivery assignment solution for swarms of UAVs dealing with multi-dimensional chromosome representation of genetic algorithm

KT San, EY Lee, YS Chang - 2016 IEEE 7th Annual Ubiquitous …, 2016 - ieeexplore.ieee.org
This paper describes the implementation steps used to assign a swarm of unmanned aerial
vehicles (UAVs) tasked to effectively deliver items to target locations. Several possible and …

General Boolean Function Benchmark Suite

R Kalkreuth, Z Vašíček, J Husa, D Vermetten… - Proceedings of the 17th …, 2023 - dl.acm.org
Just over a decade ago, the first comprehensive review on the state of benchmarking in
Genetic Programming (GP) analyzed the mismatch between the problems that are used to …

Mammogram classification using sparse-ROI: A novel representation to arbitrary shaped masses

KP Kanadam, SR Chereddy - Expert Systems with Applications, 2016 - Elsevier
Masses in breast are the important radiographic signs of cancer. Developing automated
detection of these masses is the main objective in the medical detection of breast cancer …

Recurrent cartesian genetic programming of artificial neural networks

AJ Turner, JF Miller - Genetic Programming and Evolvable Machines, 2017 - Springer
Abstract Cartesian Genetic Programming of Artificial Neural Networks is a
NeuroEvolutionary method based on Cartesian Genetic Programming. Cartesian Genetic …