Genetic programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Non-destructive Depth-Dependent Crossover for Genetic Programming
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
A new approach to evaluate GP schema in context
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Using context-aware crossover to improve the performance of GP
Proceedings of the 8th annual conference on Genetic and evolutionary computation
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
An analysis of constructive crossover and selection pressure in genetic programming
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
Towards a Less Destructive Crossover Operator Using Immunity Theory
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Testing the CAX on a Real-World Problem and Other Benchmarks
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
A survey and taxonomy of performance improvement of canonical genetic programming
Knowledge and Information Systems
Balancing Parent and Offspring Selection in Genetic Programming
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Semantics based crossover for boolean problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Robust symbolic regression with affine arithmetic
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Semantic similarity based crossover in GP: the case for real-valued function regression
EA'09 Proceedings of the 9th international conference on Artificial evolution
Semantically-based crossover in genetic programming: application to real-valued symbolic regression
Genetic Programming and Evolvable Machines
On the roles of semantic locality of crossover in genetic programming
Information Sciences: an International Journal
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Standard GP crossover is widely accepted as being a largely destructive operator, creating many poor offspring in the search for better ones. One of the major reasons for its destructiveness is its disrespect for the context of swapped subtrees in their respective parent trees when creating offspring. At times, this hampers GP's performance considerably, and results in populations with low average fitness values. 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.