Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Advances in genetic programming
Genetic programming using a minimum description length principle
Advances in genetic programming
Inductive functional programming using incremental program transformation
Artificial Intelligence
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
The evolution of size and shape
Advances in genetic programming
Genetic Programming and Evolvable Machines
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
Crossover Operators For A Hardware Implementation Of GP Using FPGAs And Handel-C
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Genetic Programming Bloat with Dynamic Fitness
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Modification point depth and genome growth in genetic programming
Evolutionary Computation
EH '99 Proceedings of the 1st NASA/DOD workshop on Evolvable Hardware
Multi-Objective Methods for Tree Size Control
Genetic Programming and Evolvable Machines
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
Problem Difficulty and Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
Resource-limited genetic programming: the dynamic approach
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Balancing accuracy and parsimony in genetic programming
Evolutionary Computation
Effects of code growth and parsimony pressure on populations in genetic programming
Evolutionary Computation
Collective adaptation: The exchange of coding segments
Evolutionary Computation
Code growth, explicitly defined introns, and alternative selection schemes
Evolutionary Computation
Putting more genetics into genetic algorithms
Evolutionary Computation
Code growth 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
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
Population variation in genetic programming
Information Sciences: an International Journal
Incorporating model identifiability into equation discovery of ODE systems
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Analysis of Population Evolution in Classifier Systems Using Symbolic Representations
Learning Classifier Systems
Classifier Conditions Using Gene Expression Programming
Learning Classifier Systems
Genetic Programming and Evolvable Machines
Characterizing fault tolerance in genetic programming
BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
How online simplification affects building blocks in genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Bloat control in genetic programming by evaluating contribution of nodes
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A survey and taxonomy of performance improvement of canonical genetic programming
Knowledge and Information Systems
ACAL '09 Proceedings of the 4th Australian Conference on Artificial Life: Borrowing from Biology
The identification and exploitation of dormancy in genetic programming
Genetic Programming and Evolvable Machines
The influence of mutation on population dynamics in multiobjective genetic programming
Genetic Programming and Evolvable Machines
Bloat control operators and diversity in genetic programming: A comparative study
Evolutionary Computation
Operator equalisation and bloat free GP
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Implicitly controlling bloat in genetic programming
IEEE Transactions on Evolutionary Computation
Evolutionary repair of faulty software
Applied Soft Computing
Variance based selection to improve test set performance in genetic programming
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Size-based tournaments for node selection
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Long memory time series forecasting by using genetic programming
Genetic Programming and Evolvable Machines
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
Sensitive ants are sensible ants
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
XCSR with computed continuous action
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Controlling bloat through parsimonious elitist replacement and spatial structure
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
Length bias and search limitations in cartesian genetic programming
Proceedings of the 15th annual conference 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
Co-evolutionary automatic programming for software development
Information Sciences: an International Journal
GP-induced and explicit bloating of the seeds in incremental GP improves evolutionary success
Genetic Programming and Evolvable Machines
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Genetic programming has highlighted the problem of bloat, the uncontrolled growth of the average size of an individual in the population. The most common approach to dealing with bloat in tree-based genetic programming individuals is to limit their maximal allowed depth. An alternative to depth limiting is to punish individuals in some way based on excess size, and our experiments have shown that the combination of depth limiting with such a punitive method is generally more effective than either alone. Which such combinations are most effective at reducing bloat? In this article we augment depth limiting with nine bloat control methods and compare them with one another. These methods are chosen from past literature and from techniques of our own devising, esting with four genetic programming problems, we identify where each bloat control method performs well on a per-problem basis, and under what settings various methods are effective independent of problem. We report on the results of these tests, and discover an unexpected winner in the cross-platform category.