An algebraic equation for the halting probability
A half-century survey on The Universal Turing Machine
Foundations of genetic programming
Foundations of genetic programming
Using Schema Theory To Explore Interactions Of Multiple Operators
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Convergence Rates For The Distribution Of Program Outputs
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Visualizing Tree Structures in Genetic Programming
Genetic Programming and Evolvable Machines
Convergence of program fitness landscapes
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
On the behavioral diversity of random programs
Proceedings of the 9th annual conference on Genetic and evolutionary computation
The impact of population size on code growth in GP: analysis and empirical validation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Mapping non-conventional extensions of genetic programming
UC'06 Proceedings of the 5th international conference on Unconventional Computation
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Theoretical models of Turing complete linear genetic programming (GP) programs suggest the fraction of halting programs is vanishingly small. Convergence results proved for an idealised machine, are tested on a small T7 computer with (finite) memory, conditional branches and jumps. Simulations confirm Turing complete fitness landscapes of this type hold at most a vanishingly small fraction of usable solutions.