Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Some Considerations on the Reason for Bloat
Genetic Programming and Evolvable Machines
A Metric for Genetic Programs and Fitness Sharing
Proceedings of the European Conference on Genetic Programming
Deriving Genetic Programming Fitness Properties by Static Analysis
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
Redundant representations in evolutionary computation
Evolutionary Computation
Genetic Programming and Model Checking: Synthesizing New Mutual Exclusion Algorithms
ATVA '08 Proceedings of the 6th International Symposium on Automated Technology for Verification and Analysis
On Improving Generalisation in Genetic Programming
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Semantic Aware Crossover for Genetic Programming: The Case for Real-Valued Function Regression
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Using crossover based similarity measure to improve genetic programming generalization ability
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Dynamic maximum tree depth: a simple technique for avoiding bloat in tree-based GP
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Genetic programming with fitness based on model checking
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Model checking-based genetic programming with an application to mutual exclusion
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
Semantic similarity based crossover in GP: the case for real-valued function regression
EA'09 Proceedings of the 9th international conference on Artificial evolution
Genetic programming, validation sets, and parsimony pressure
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
On the locality of grammatical evolution
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
An attribute grammar decoder for the 01 multiconstrained knapsack problem
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Improving the generalisation ability of genetic programming with semantic similarity based crossover
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
Representation and structural difficulty in genetic programming
IEEE Transactions on Evolutionary Computation
A new implementation of geometric semantic GP and its application to problems in pharmacokinetics
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
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This paper investigates the role of syntactic locality and semantic locality of crossover in Genetic Programming (GP). First we propose a novel crossover using syntactic locality, Syntactic Similarity based Crossover (SySC). We test this crossover on a number of real-valued symbolic regression problems. A comparison is undertaken with Standard Crossover (SC), and a recently proposed crossover for improving semantic locality, Semantic Similarity based Crossover (SSC). The metrics analysed include GP performance, GP code bloat and the effect on the ability of GP to generalise. The results show that improving syntactic locality reduces code bloat, and that leads to a slight improvement of the ability to generalise. By comparison, improving semantic locality significantly enhances GP performance, reduces code bloat and substantially improves the ability of GP to generalise. These results comfirm the more important role of semantic locality for crossover in GP.