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EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
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GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
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EuroGP'07 Proceedings of the 10th European conference on Genetic programming
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IEEE Transactions on Evolutionary Computation
The Automatic Acquisition, Evolution and Reuse of Modules in Cartesian Genetic Programming
IEEE Transactions on Evolutionary Computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
On the Effectiveness of Evolution Compared to Time-Consuming Full Search of Optimal 6-State Automata
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
GECCO 2011 tutorial: cartesian genetic programming
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Using Cartesian genetic programming to design wire antenna
International Journal of Computer Applications in Technology
GECCO 2012 tutorial: cartesian genetic programming
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
GECCO 2013 tutorial: cartesian genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Function optimization using cartesian genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) have been applied to real-valued function optimisation. Both of these techniques directly evolve the real-values that are the arguments of the real-valued function. In this paper we have applied a form of genetic programming called Cartesian Genetic Programming (CGP) to a number of real-valued optimisation benchmark problems. The approach we have taken is to evolve a computer program that controls a writing-head, which moves along and interacts with a finite set of symbols that are interpreted as real numbers, instead of manipulating the real numbers directly. In other studies, CGP has already been shown to benefit from a high degree of neutrality. We hope to exploit this for real-valued function optimisation problems to avoid being trapped on local optima. We have also used an extended form of CGP called Embedded CGP (ECGP) which allows the acquisition, evolution and re-use of modules. The effectiveness of CGP and ECGP are compared and contrasted with CEP and FEP on the benchmark problems. Results show that the new techniques are very effective.