Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
An Analysis of Hierarchical Genetic Programming
An Analysis of Hierarchical Genetic Programming
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
What Makes a Problem GP-Hard? Analysis of a Tunably Difficult Problem in Genetic Programming
Genetic Programming and Evolvable Machines
Genetic Programming: A Review of Some Concerns
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
Modification point depth and genome growth in genetic programming
Evolutionary Computation
Visualizing Tree Structures 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
Probing for limits to building block mixing with a tunably-difficult problem for genetic programming
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetic programming: parametric analysis of structure altering mutation techniques
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming
Evolutionary Computation
ORDERTREE: a new test problem for genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A comparison of bloat control methods for genetic programming
Evolutionary Computation
Introducing probabilistic adaptive mapping developmental genetic programming with redundant mappings
Genetic Programming and Evolvable Machines
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Effects of code growth and parsimony pressure on populations in genetic programming
Evolutionary Computation
Genetic Programming and Evolvable Machines
Binary encoding for prototype tree of probabilistic model building GP
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
IEEE Transactions on Evolutionary Computation
Visualizing tree structures 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
Difficulty of unimodal and multimodal landscapes in genetic programming
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
Genetic programming for attribute construction in data mining
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Fitness distance correlation in structural mutation genetic programming
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Efficiently evolving programs through the search for novelty
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Semantics based crossover for boolean problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Sampling bias in estimation of distribution algorithms for genetic programming using prototype trees
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Reducing overfitting in genetic programming models for software quality classification
HASE'04 Proceedings of the Eighth IEEE international conference on High assurance systems engineering
Examining mutation landscapes in grammar based genetic programming
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Investigation of the performance of different mapping orders for GE on the max problem
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
The tree-string problem: an artificial domain for structure and content search
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
Genetic programming needs better benchmarks
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
The max problem revisited: the importance of mutation in genetic programming
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Better GP benchmarks: community survey results and proposals
Genetic Programming and Evolvable Machines
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The Crossover operator is common to most implementations of Genetic Programming (GP). Often, there is some form of restriction on the size of trees in the GP population. This paper concentrates on the interaction between the standard crossover operator and a restriction on tree depth demonstrated by the MAX problem, which involves returning the largest possible value for given function and terminal sets and maximum tree depth. Some characteristics and inadequacies of crossover in normal use are highlighted and discussed. Subtree discovery and movement takes place mostly near the leaf nodes, with nodes near the root left untouched, where diversity drops quickly to zero in the tree population. GP is then unable to create fitter trees via the crossover operator, leaving a mutation operator as the only common, but ineffective, route to discovery of fitter trees.