Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Crossover in Grammatical Evolution
Genetic Programming and Evolvable Machines
Ripple Crossover in Genetic Programming
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
GEVA: grammatical evolution in Java
ACM SIGEVOlution
Structural and nodal mutation in grammatical evolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Foundations in Grammatical Evolution for Dynamic Environments
Foundations in Grammatical Evolution for Dynamic Environments
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
On the locality of grammatical evolution
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
A symbolic regression approach to manage femtocell coverage using grammatical genetic programming
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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 genotype-phenotype maps in grammatical evolution
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
A local search interface for interactive evolutionary architectural design
EvoMUSART'12 Proceedings of the First international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
Evolving femtocell algorithms with dynamic and stationary training scenarios
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
A comparison of grammatical genetic programming grammars for controlling femtocell network coverage
Genetic Programming and Evolvable Machines
A methodology for user directed search in evolutionary design
Genetic Programming and Evolvable Machines
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This study attempts to decompose the behaviour of mutation in Grammatical Evolution (GE). Standard GE mutation can be divided into two types of events, those that are structural in nature and those that are nodal. A structural event can alter the length of the phenotype whereas a nodal event simply alters the value at any terminal (leaf or internal node) of a derivation tree. We analyse the behaviour of standard mutation and compare it to the behaviour of its nodal and structural components. These results are then compared with standard GP operators to see how they differ. This study increases our understanding of how the search operators of an evolutionary algorithm behave.