Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
The evolution of evolvability in genetic programming
Advances in genetic programming
Genetic programming and emergent intelligence
Advances in genetic programming
Two self-adaptive crossover operators for genetic programming
Advances in genetic programming
Explicitly defined introns and destructive crossover in genetic programming
Advances in genetic programming
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Accurate Replication in Genetic Programming
Proceedings of the 6th International Conference on Genetic Algorithms
Complexity Compression and Evolution
Proceedings of the 6th International Conference on Genetic Algorithms
A study in program response and the negative effects of introns in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
How neutral networks influence evolvability
Complexity
Controlling effective introns for multi-agent learning by means of genetic programming
Soft computing agents
Biomimetic Representation with Genetic Programming Enzyme
Genetic Programming and Evolvable Machines
An Analysis of the Causes of Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
Genetic Programming Bloat without Semantics
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Exons and Code Growth in Genetic Programming
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Modification point depth and genome growth in genetic programming
Evolutionary Computation
Problem Difficulty and Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
Dormant program nodes and the efficiency of genetic programming
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Function choice, resiliency and growth in genetic programming
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Resilient Individuals Improve Evolutionary Search
Artificial Life
Comparing genetic robustness in generational vs. steady state evolutionary algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Growth of self-canceling code in evolutionary systems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A comparison of bloat control methods for genetic programming
Evolutionary Computation
Eliminating Introns in Ant Colony Programming
Fundamenta Informaticae
Neutral offspring controlling operators in genetic programming
Pattern Recognition
A GP neutral function for the artificial ANT problem
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Genetic Programming and Evolvable Machines
The identification and exploitation of dormancy in genetic programming
Genetic Programming and Evolvable Machines
Positional independence and recombination in cartesian genetic programming
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
Eliminating Introns in Ant Colony Programming
Fundamenta Informaticae
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Previous work on introns and code growth in genetic programming is expanded on and tested experimentally. Explicitly defined introns are introduced to tree-based representations as an aid to measuring and evaluating intron behavior. Although it is shown that introns do create code growth, they are not its only cause. Removing introns merely decreases the growth rate; it does not eliminate it. By systematically negating various forms of intron behavior, a deeper understanding of the causes of code growth is obtained, leading to the development of a system that keeps unnecessary bloat to a minimum. Alternative selection schemes and recombination operators are examined and improvements demonstrated over the standard selection methods in terms of both performance and parsimony.