The connection machine
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic programming and emergent intelligence
Advances in genetic programming
Advances in genetic programming
Recombination, selection, and the genetic construction of computer programs
Recombination, selection, and the genetic construction of computer programs
The evolution of size and shape
Advances in genetic programming
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
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
An Empirical Study of Multipopulation Genetic Programming
Genetic Programming and Evolvable Machines
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
The ECOlogical Framework II: Improving GA Performance At Virtually Zero Cost
Proceedings of the 5th International Conference on Genetic Algorithms
Structure and Performance of Fine-Grain Parallelism in Genetic Search
Proceedings of the 5th International Conference on Genetic Algorithms
Genetic Programming for Feature Discovery and Image Discrimination
Proceedings of the 5th International Conference on Genetic Algorithms
On Decentralizing Selection Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
Evolving Data Structures with 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
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
Comparing Synchronous and Asynchronous Parallel and Distributed Genetic Programming Models
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Modification point depth and genome growth in genetic programming
Evolutionary Computation
General schema theory for genetic programming with subtree-swapping crossover: Part II
Evolutionary Computation
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
Resource-limited genetic programming: the dynamic approach
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Algebraic simplification of GP programs during evolution
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A comparison of bloat control methods for genetic programming
Evolutionary Computation
Studying the influence of synchronous and asynchronous parallel GP on programs length evolution
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Balancing accuracy and parsimony in genetic programming
Evolutionary Computation
Evolutionary dynamics for the spatial Moran process
Genetic Programming and Evolvable Machines
Elitism reduces bloat in genetic programming
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Code growth 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
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
A SIMD interpreter for genetic programming on GPU graphics cards
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
Population parallel GP on the G80 GPU
EuroGP'08 Proceedings of the 11th European conference on Genetic programming
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Dynamic size populations in distributed genetic programming
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Parallel genetic algorithms on programmable graphics hardware
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Genetic evolution of controllers for challenging control problems
Journal of Computational Methods in Sciences and Engineering
Controlling bloat through parsimonious elitist replacement and spatial structure
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
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During the evolution of solutions using genetic programming (GP) there is generally an increase in average tree size without a corresponding increase in fitness--a phenomenon commonly referred to as bloat. Although previously studied from theoretical and practical viewpoints there has been little progress in deriving controls for bloat which do not explicitly refer to tree size. Here, the use of spatial population structure in combination with local elitist replacement is shown to reduce bloat without a subsequent loss of performance. Theoretical concepts regarding inbreeding and the role of elitism are used to support the described approach. The proposed system behavior is confirmed via extensive computer simulations on benchmark problems. The main practical result is that by placing a population on a torus, with selection defined by a Moore neighborhood and local elitist replacement, bloat can be substantially reduced without compromising performance.