Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines
Complexity Compression and Evolution
Proceedings of the 6th International Conference on Genetic Algorithms
Proceedings of the 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
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Strongly typed genetic programming
Evolutionary Computation
Schema theory for genetic programming with one-point crossover and point mutation
Evolutionary Computation
Schemata evolution and building blocks
Evolutionary Computation
Genetic Programming and Evolvable Machines
Genetic Programming for Classification: An Analysis of Convergence Behaviour
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
Smooth Uniform Crossover with Smooth Point Mutation in Genetic Programming: A Preliminary Study
Proceedings of the Second European Workshop 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
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Sub-machine-code GP: New Results and Extensions
Proceedings of the Second European Workshop on Genetic Programming
General schema theory for genetic programming with subtree-swapping crossover: part I
Evolutionary Computation
General schema theory for genetic programming with subtree-swapping crossover: Part II
Evolutionary Computation
Visualizing Tree Structures in Genetic Programming
Genetic Programming and Evolvable Machines
An extension of vose's markov chain model for genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Probing for limits to building block mixing with a tunably-difficult problem for genetic programming
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Characterizing the dynamics of symmetry breaking in genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Evolutionary Computation
Proceedings of the 10th 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
Genetic Programming and Evolvable Machines
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
A simple but theoretically-motivated method to control bloat in genetic programming
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Bloat control operators and diversity in genetic programming: A comparative study
Evolutionary Computation
Theoretical results in genetic programming: the next ten years?
Genetic Programming and Evolvable Machines
Tarpeian bloat control and generalization accuracy
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
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In this paper a new, general and exact schema theory for genetic programming is presented. The theory includes a microscopic schema theorem applicable to crossover operators which replace a subtree in one parent with a sub-tree from the other parent to produce the offspring. A more macroscopic schema theorem is also provided which is valid for crossover operators in which the probability of selecting any two crossover points in the parents depends only on their size and shape. The theory is based on the notions of Cartesian node reference systems and variable-arity hyperschemata both introduced here for the first time. In the paper we provide examples which show how the theory can be specialised to specific crossover operators and how it can be used to derive an exact definition of effective fitness and a size-evolution equation for GP.