Name
Abstract | ||
|---|---|---|
The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm being unable to find the global optimum. We present a new method of approximating the genetic similarity between two individuals using ancestry information. We define a new diversity-preserving selection scheme, based on standard tournament selection, which encourages genetically dissimilar individuals to undergo genetic operation. The new method is illustrated by assessing its performance in a well-known problem domain: algebraic symbolic regression. |
Year | Venue | Keywords |
|---|---|---|
2003 | GECCO | greater chance,new diversity-preserving selection scheme,genetic operation,algebraic symbolic regression,dissimilar individual,ancestry information,genetic programming,genetic similarity,new method,ancestry-based mate selection scheme,standard tournament selection,genetics,genetic operator,mate selection |
Field | DocType | Volume |
Genetic operator,Truncation selection,Computer science,Fitness proportionate selection,Genetic programming,Genetic representation,Artificial intelligence,Selection (genetic algorithm),Symbolic regression,Tournament selection,Machine learning | Conference | 2724 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-40603-4 | 1 |
PageRank | References | Authors |
0.34 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rodney Fry | 1 | 7 | 0.84 |
| Andy Tyrrell | 2 | 158 | 13.74 |