Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Explicitly defined introns and destructive crossover in genetic programming
Advances in genetic programming
The evolution of size and shape
Advances in genetic programming
Foundations of genetic programming
Foundations of genetic programming
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
An Analysis of the Causes of Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
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
Finding Needles in Haystacks Is Not Hard with Neutrality
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Code growth in genetic programming
Code growth in genetic programming
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
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
Dynamics of evolutionary robustness
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Genetic programming for medical classification: a program simplification approach
Genetic Programming and Evolvable Machines
Exploiting the path of least resistance in evolution
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Genetic Programming and Evolvable Machines
How online simplification affects building blocks in genetic programming
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
IEEE Transactions on Evolutionary Computation
A survey and taxonomy of performance improvement of canonical genetic programming
Knowledge and Information Systems
Implicitly controlling bloat in genetic programming
IEEE Transactions on Evolutionary Computation
A relaxed approach to simplification in genetic programming
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
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This paper discusses the underlying pressures responsible for code growth in genetic programming, and shows how an understanding of these pressures can be used to use to eliminate code growth while simultaneously improving performance. We begin with a discussion of two distinct components of code growth and the extent to which each component is relevant in practice. We then define the concept of resilience in GP trees, and show that the buildup of resilience is essential for code growth. We present simple modifications to the selection procedures used by GP that eliminate bloat without hurting performance. Finally, we show that eliminating bloat can improve the performance of genetic programming by a factor that increases as the problem is scaled in difficulty.