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CEC
2009
IEEE
14 years 2 months ago
Implicit Context Representation Cartesian Genetic Programming for the assessment of visuo-spatial ability
— In this paper, a revised form of Implicit Context Representation Cartesian Genetic Programming is used in the development of a diagnostic tool for the assessment of patients wi...
Stephen L. Smith, Michael A. Lones
EUROGP
2009
Springer
138views Optimization» more  EUROGP 2009»
14 years 2 months ago
Self Modifying Cartesian Genetic Programming: Fibonacci, Squares, Regression and Summing
Self Modifying CGP (SMCGP) is a developmental form of Cartesian Genetic Programming(CGP). It is able to modify its own phenotype during execution of the evolved program. This is do...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
GECCO
2008
Springer
201views Optimization» more  GECCO 2008»
13 years 8 months ago
Advanced techniques for the creation and propagation of modules in cartesian genetic programming
The choice of an appropriate hardware representation model is key to successful evolution of digital circuits. One of the most popular models is cartesian genetic programming, whi...
Paul Kaufmann, Marco Platzner
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
13 years 11 months ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
14 years 1 months ago
Self-modifying cartesian genetic programming
In nature, systems with enormous numbers of components (i.e. cells) are evolved from a relatively small genotype. It has not yet been demonstrated that artificial evolution is su...
Simon Harding, Julian Francis Miller, Wolfgang Ban...