Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Studies in artificial evolution
Studies in artificial evolution
Genetic programming in C++: implementation issues
Advances in genetic programming
Explicitly defined introns and destructive crossover in genetic programming
Advances in genetic programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Proceedings of the Genetic and Evolutionary Computation Conference
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Crossover in Grammatical Evolution: A Smooth Operator?
Proceedings of the European Conference on Genetic Programming
Crossover in Grammatical Evolution: The Search Continues
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Grammatical Evolution: Evolving Programs for an Arbitrary Language
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
Ripple Crossover in Genetic Programming
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Grammatical bias for evolutionary learning
Grammatical bias for evolutionary learning
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Meta-grammar constant creation with grammatical evolution by grammatical evolution
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Constant creation in grammatical evolution
International Journal of Innovative Computing and Applications
Evolving encapsulated programs as shared grammars
Genetic Programming and Evolvable Machines
Shape grammars and grammatical evolution for evolutionary design
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Structural and nodal mutation in grammatical evolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
CIMMACS'09 Proceedings of the 8th WSEAS International Conference on Computational intelligence, man-machine systems and cybernetics
Grammar-based Genetic Programming: a survey
Genetic Programming and Evolvable Machines
Particle swarm optimization models applied to neural networks using the R language
WSEAS TRANSACTIONS on SYSTEMS
A fine-grained view of GP locality with binary decision diagrams as ant phenotypes
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
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
An analysis of the behaviour of mutation in grammatical evolution
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
Evolving dynamic trade execution strategies using grammatical evolution
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
Evolving trading rule-based policies
EvoCOMNET'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part II
Graph grammars as a representation for interactive evolutionary 3d design
EvoMUSART'12 Proceedings of the First international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Constituent grammatical evolution
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
GEARNet: grammatical evolution with artificial regulatory networks
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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We present an investigation into crossover in Grammatical Evolution that begins by examining a biologically-inspired homologous crossover operator that is compared to standard one and two-point operators. Results demonstrate that this homologous operator is no better than the simpler one-point operator traditionally adopted.An analysis of the effectiveness of one-point crossover is then conducted by determining the effects of this operator, by adopting a headless chicken-type crossover that swaps randomly generated fragments in place of the evolved strings. Experiments show detrimental effects with the utility of the headless chicken operator.Finally, the mechanism of crossover in GE is analysed and termed ripple crossover, due to its defining characteristics. An experiment is described where ripple crossover is applied to tree-based genetic programming, and the results show that ripple crossover is more effective in exploring the search space of possible programs than sub-tree crossover by examining the rate of premature convergence during the run. Ripple crossover produces populations whose fitness increases gradually over time, slower than, but to an eventual higher level than that of sub-tree crossover.