Created by W.Langdon from gp-bibliography.bib Revision:1.8129
Many attempts have been made to make it a more constructive crossover, mostly by preserving the context of the selected subtree in the offspring. Although successful at preserving context, none of these methods provide the opportunity to discover new and better contexts for exchanged subtrees.
We introduce a context-aware crossover operator which operates by identifying all possible contexts for a subtree, and evaluating each of them. The context that produces the highest fitness is used to create a child which is then passed into the next generation.
We have tested its performance on many benchmark problems. It has shown better results than the standard GP crossover operator, using either the same number or fewer individual evaluations. Furthermore, the average fitness of populations using this scheme improves considerably, and programs produced in this way are much smaller than those produced using standard crossover.",
Variation in operator frequencies from beginning to end of GP run.",
Genetic Programming entries for Hammad Majeed Conor Ryan