Genetic programming and emergent intelligence
Advances in genetic programming
Extending genetic programming with recombinative guidance
Advances in genetic programming
Discovery of subroutines in genetic programming
Advances in genetic programming
Context-aware mutation: a modular, context aware mutation operator for genetic programming
Proceedings of the 9th annual conference on Genetic and evolutionary computation
On the constructiveness of context-aware crossover
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Seeding methods for run transferable libraries
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Potential fitness for genetic programming
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
On relationships between semantic diversity, complexity and modularity of programming tasks
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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We propose a new methodology to look at the fitness contributions (semantics) of different schemata in Genetic Programming (GP). We hypothesize that the significance of a schema can be evaluated by calculating its fitness contribution to the total fitness of the trees that contain it, and use our methodology to test this hypothesis.It is shown that this method can also be used to identify schemata that are important in terms of both individual runs and individual problems (that is, schema that will be important across many runs on a particular problem).The usefulness of this study to existing schema theories and its effective use in the detection of introns, in the identification of potentially useful modular functions are also discussed in this paper.