Weighted lagrange distributions and their characterizations
SIAM Journal on Applied Mathematics
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
Recombination, selection, and the genetic construction of computer programs
Recombination, selection, and the genetic construction of computer programs
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
A historical perspective on the evolution of executable structures
Fundamenta Informaticae
The evolution of size and shape
Advances in genetic programming
Foundations of genetic programming
Foundations of genetic programming
Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming!
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines
Some Considerations on the Reason for Bloat
Genetic Programming and Evolvable Machines
An Analysis of the Causes of Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
Generality and Difficulty in Genetic Programming: Evolving a Sort
Proceedings of the 5th International Conference on Genetic Algorithms
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
Fighting Bloat with Nonparametric Parsimony Pressure
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Lexicographic Parsimony Pressure
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
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
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Fitness Causes Bloat: Mutation
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Modification point depth and genome growth in genetic programming
Evolutionary Computation
Code growth in genetic programming
Code growth in genetic programming
Problem Difficulty and Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
Exploiting disruption aversion to control code bloat
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Resource-limited genetic programming: the dynamic approach
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A statistical learning theory approach of bloat
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Proceedings of the 8th annual conference on Genetic and evolutionary computation
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
Code growth, explicitly defined introns, and alternative selection schemes
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
Elitism reduces bloat in genetic programming
Proceedings of the 10th annual conference on Genetic and evolutionary computation
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
An adverse interaction between crossover and restricted tree depth in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Generality versus size in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Population implosion in genetic programming
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Dynamic maximum tree depth: a simple technique for avoiding bloat in tree-based GP
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
Neutral variations cause bloat in linear GP
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
The effect of plagues in genetic programming: a study of variable-size populations
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
The root causes of code growth 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
Crossover, sampling, bloat and the harmful effects of size limits
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Dynamic size populations in distributed genetic programming
EuroGP'05 Proceedings of the 8th 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
How online simplification affects building blocks in genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
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
Measuring bloat, overfitting and functional complexity in genetic programming
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Predicting problem difficulty for genetic programming applied to data classification
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Reassembling operator equalisation: a secret revealed
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Bloat control in genetic programming with a histogram-based accept-reject method
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Size-based tournaments for node selection
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
A quantitative study of learning and generalization in genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
An empirical study of functional complexity as an indicator of overfitting in genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Estimating classifier performance with genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Macro-economic time series modeling and interaction networks
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part II
Reassembling operator equalisation: a secret revealed
ACM SIGEVOlution
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
Improving the parsimony of regression models for an enhanced genetic programming process
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Random sampling technique for overfitting control in genetic programming
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
Lévy-Flight genetic programming: towards a new mutation paradigm
EvoBIO'12 Proceedings of the 10th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
Evolving estimators of the pointwise Hölder exponent with Genetic Programming
Information Sciences: an International Journal
Genetic programming needs better benchmarks
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
Balancing learning and overfitting in genetic programming with interleaved sampling of training data
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
Prediction of forest aboveground biomass: an exercise on avoiding overfitting
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
A behavior-based analysis of modal problems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
A bootstrapping approach to reduce over-fitting in genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Bloat is an excess of code growth without a corresponding improvement in fitness. This is a serious problem in Genetic Programming, often leading to the stagnation of the evolutionary process. Here we provide an extensive review of all the past and current theories regarding why bloat occurs. After more than 15 years of intense research, recent work is shedding new light on what may be the real reasons for the bloat phenomenon. We then introduce Dynamic Limits, our new approach to bloat control. It implements a dynamic limit that can be raised or lowered, depending on the best solution found so far, and can be applied either to the depth or size of the programs being evolved. Four problems were used as a benchmark to study the efficiency of Dynamic Limits. The quality of the results is highly dependent on the type of limit used: depth or size. The depth variants performed very well across the set of problems studied, achieving similar fitness to the baseline technique while using significantly smaller trees. Unlike many other methods available so far, Dynamic Limits does not require specific genetic operators, modifications in fitness evaluation or different selection schemes, nor does it add any parameters to the search process. Furthermore, its implementation is simple and its efficiency does not rely on the usage of a static upper limit. The results are discussed in the context of the newest bloat theory.