The complexity of Boolean functions
The complexity of Boolean functions
Elements of information theory
Elements of information theory
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Foundations of genetic programming
Foundations of genetic programming
Proceedings of the European Conference on Genetic Programming
Toward simulated evolution of machine-language iteration
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
No free lunch, program induction and combinatorial problems
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Investigating the performance of module acquisition in cartesian genetic programming
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
No free lunch, program induction and combinatorial problems
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Analysing the regularity of genomes using compression and expression simplification
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Evolvability via modularity-induced mutational focussing
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Theoretical results in genetic programming: the next ten years?
Genetic Programming and Evolvable Machines
Open issues in genetic programming
Genetic Programming and Evolvable Machines
Complexity and cartesian genetic programming
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Invariance of function complexity under primitive recursive functions
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
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Genetic Programming uses a tree based representation to express solutions to problems. Trees are constructed from a primitive set which consists of a function set and a terminal set. An extension to GP is the ability to define modules, which are in turn tree based representations defined in terms of the primitives. The most well known of these methods is Koza's Automatically Defined Functions. In this paper it is proved that for a given problem, the minimum number of nodes in the main tree plus the nodes in any modules is independent of the primitive set (up to an additive constant) and depends only on the function being expressed. This reduces the number of user defined parameters in the run and makes the inclusion of a hypothesis in the search space independent of the primitive set.