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 size and shape
Advances in genetic programming
Foundations of genetic programming
Foundations of genetic programming
Digital Picture Processing
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Accurate Replication in Genetic Programming
Proceedings of the 6th International Conference on Genetic Algorithms
Random Tree Generation for Genetic Programming
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Size Control Via Size Fair Genetic Operators In The PushGP Genetic Programming System
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
A comparison of bloat control methods for genetic programming
Evolutionary Computation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Balancing accuracy and parsimony in genetic programming
Evolutionary Computation
Evolutionary induction of sparse neural trees
Evolutionary Computation
Effects of code growth and parsimony pressure on populations in genetic programming
Evolutionary Computation
A simple but theoretically-motivated method to control bloat in genetic programming
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
On the limiting distribution of program sizes in tree-based genetic programming
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Extending Operator Equalisation: Fitness Based Self Adaptive Length Distribution for Bloat Free GP
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Semantic Aware Crossover for Genetic Programming: The Case for Real-Valued Function Regression
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Operator equalisation, bloat and overfitting: a study on human oral bioavailability prediction
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Using Operator Equalisation for Prediction of Drug Toxicity with Genetic Programming
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
ACAL '09 Proceedings of the 4th Australian Conference on Artificial Life: Borrowing from Biology
Measuring bloat, overfitting and functional complexity in genetic programming
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Theoretical results in genetic programming: the next ten years?
Genetic Programming and Evolvable Machines
Reassembling operator equalisation: a secret revealed
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Reassembling operator equalisation: a secret revealed
ACM SIGEVOlution
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Sub-tree swapping crossover and arity histogram distributions
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
A relaxed approach to simplification in genetic programming
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
Spatial co-evolution: quicker, fitter and less bloated
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Computational complexity analysis of multi-objective genetic programming
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Bloat free genetic programming: application to human oral bioavailability prediction
International Journal of Data Mining and Bioinformatics
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Research has shown that beyond a certain minimum program length the distributions of program functionality and fitness converge to a limit. Before that limit, however, there may be program-length classes with a higher or lower average fitness than that achieved beyond the limit. Ideally, therefore, GP search should be limited to program lengths that are within the limit and that can achieve optimum fitness. This has the dual benefits of providing the simplest/smallest solutions and preventing GP bloat thus shortening run times. Here we introduce a novel and simple technique, which we call Operator Equalisation, to control how GP will sample certain length classes. This allows us to finely and freely bias the search towards shorter or longer programs and also to search specific length classes during a GP run. This gives the user total control on the program length distribution, thereby completely freeing GP from bloat. Results show that we can automatically identify potentially optimal solution length classes quickly using small samples and that, for particular classes of problems, simple length biases can significantly improve the best fitness found during a GP run.