I think therefore I CGP
Julian Miller and Andy Turner are giving a tutorial on Cartesian Genetic Programming at GECCO 2015 (Madrid)
At the Evostar 2015 Conference there were a number of papers which used CGP.
Cartesian GP in Optimization of Combinational Circuits with Hundreds of Inputs and Thousands of Gates
Evolutionary Design of Transistor Level Digital Circuits Using Discrete Simulation
Vojtech Mrazek and Zdenek Vasicek
Indirectly Encoded Fitness Predictors Coevolved with Cartesian Programs
Michaela Sikulova, Jiri Hulva, and Lukas Sekanina
Evolutionary Methods for the Construction of Cryptographic Boolean Functions
Stjepan Picek, Domagoj Jakobovic1, Julian F. Miller, Elena Marchiori and Lejla Batina
Circuit Approximation Using Single- and Multi-objective Cartesian GP
Zdenek Vasicek and Lukas Sekanina
A Fast FPGA-Based Classification of Application Protocols Optimized Using Cartesian GP
David Grochol, Lukas Sekanina, Martin Zadnik, and Jan Korenek
A number of events related to CGP happening in 2014 at the Parallel Problem Solving from Nature conference.
PPSN 2014 (Ljubljana, Slovenia)
Julian Miller is giving a tutorial on Cartesian Genetic Programming.
Andy Turner and Julian Miller had a paper on
Recurrent Cartesian Genetic Programming.
There are two other papers on evolving solutions to computational problems using materials (e.g. carbon nanotubes) where CGP has been used for comparative purposes
Evolution-In-Materio: Solving Machine Learning Classification Problems Using Materials.
Maktuba Mohid, Julian F. Miller, Simon L. Harding, Gunnar Tufte, Odd Rune Lykkebo, Kieran Massey, and Mike Petty.
Travelling Salesman Problem solved 'in materio' by evolved carbon nanotube device.
Kester Dean Clegg, Julian Francis Miller, Kieran Massey, and Mike Petty.
Bent Function Synthesis by Means of Cartesian Genetic Programming.
Radek Hrbacek and Vaclav Dvorak (this work resulted in a human-competitive award at GECCO 2015).
Evostar 2014 (Granada,Spain)
There were 2 papers relating to CGP at the Evostar Conference.
Cartesian Genetic Programming: Why No Bloat? Andrew Turner, Julian F. Miller
On Evolution of Multi-Category Pattern Classifiers Suitable for Embedded Systems. Zdenek Vasicek, Michal Bidlo
AISB50 (Goldsmith's College,London, UK)
At the 50th anniversary AISB conference there was a paper on CGP artificial neural networks
The Importance of Transfer Function Evolution and Heterogeneous Networks Andrew Turner, Julian F. Miller
AI2013 (Peterhouse College,Cambridge, UK)
In December 2013 the 34th SGAI International Conference on Artificial Intelligence took place in Cambridge. There was a paper on CGP artificial neural networks
The Importance of Topology Evolution in NeuroEvolution: A Case Study using Cartesian Genetic Programming of Artificial Neural Networks
Andrew Turner, Julian F. Miller
CGP Image Filters
CGP is being used in a European robotics project. Simon Harding has developed a neat way of using CGP to evolve object recognition image filters. Once the filters are evolved, they can operate extremely fast and can pick out objects of interest in images. The filters are orientation independent and still work very well under different lighting conditions. There is a nice video at IM-CLeVeR European project Here is an video of an evolved object recognition program. It detects a packet of tea!. It can detect the packet in any orientation, proximity and lighting condition.
Google Lunar X prize
CGP is being used by a team who are aiming to win the Google Lunar X prize. This is a prize awarded to the first private venture to land a rover vehicle on the moon. Wes Faler, who is a member of a team called "Part-time scientists" are building a rover called "Asimov 1". Wes gave talks at a conference called 28C3 in Berlin, Germany about two ways he is using CGP in the project. His talks are available on his blog
Look at the "People" tab for places to download these papers.
If you have news about CGP and want it linked here, please inform Julian Miller.
Zdenek Vasicek won the best paper award at EuroGP 2014 in Copenhagen for his work on speeding up and improving the optimization of industry standard benchmark electronics circuits. The resulting circuits were, on average, 34% better than the previously known minimal circuits. The circuits have hundreds of inputs and thousands of gates. Impressive work!
Andrew Turner has released an easy to use open source C implementation of CGP and Eduardo Pedroni has released a Java implementation(see the resources page). Now you have no excuse not to do CGP!