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
The evolution of evolvability in genetic programming
Advances in genetic programming
An introduction to the analysis of algorithms
An introduction to the analysis of algorithms
Hierarchical learning with procedural abstraction mechanisms
Hierarchical learning with procedural abstraction mechanisms
The evolution of size and shape
Advances in genetic programming
Random Generation of Trees: Random Generators in Computer Science
Random Generation of Trees: Random Generators in Computer Science
Strongly typed genetic programming
Evolutionary Computation
Search bias, language bias and genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines
Long Random Linear Programs Do Not Generalize
Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines
Some Considerations on the Reason for Bloat
Genetic Programming and Evolvable Machines
Genetic Programming Bloat without Semantics
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Boolean Functions Fitness Spaces
Proceedings of the Second European Workshop on Genetic Programming
Polymorphism and Genetic Programming
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
A Schema Theory Analysis of the Evolution of Size in Genetic Programming with Linear Representations
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
General schema theory for genetic programming with subtree-swapping crossover: Part II
Evolutionary Computation
Canonical representation genetic programming
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
What makes a problem GP-hard? validating a hypothesis of structural causes
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A simple but theoretically-motivated method to control bloat in genetic programming
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
No free lunch, program induction and combinatorial problems
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Elementary bit string mutation landscapes
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
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We investigate the distribution of fitness of programs concentrating on those represented as parse trees and, particularly, how such distributions scale with respect to changes in the size of the programs. By using a combination of enumeration and Monte Carlo sampling on a large number of problems from three very different areas, we suggest that, in general, once some minimum size threshold has been exceeded, the distribution of performance is approximately independent of program length. We proof this for both linear programs and simple side effect free parse trees. We give the density of solutions to the parity problems in program trees which are composed of XOR building blocks. Limited experiments with programs including side effects and iteration suggest a similar result may also hold for this wider class of programs.