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
Discovery of subroutines in genetic programming
Advances in genetic programming
Schema theory for genetic programming with one-point crossover and point mutation
Evolutionary Computation
Using context-aware crossover to improve the performance of GP
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Towards identifying salient patterns in genetic programming individuals
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Empirical analysis of GP tree-fragments
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
A less destructive, context-aware crossover operator for GP
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
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Evaluating GP schema in context is considered to be a complex, and, at times impossible, task. The tightly linked nodes of a GP tree is the main reason behind its complexity.This paper presents a new approach to evaluate GP schema in context. It is simple in its implementation with a potential to address well-known GP problems, such as identification of significant schema, dead code (introns) and module acquisition to name a few.It is based on the principle that the contribution of a schema can be evaluated by neutralizing the effect of the schema in the tree containing it (container-tree) and then checking its effect on the container-tree's fitness. Its usefulness is empirically demonstrated along with its limitation.