Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation
Machine Learning - Special issue on genetic algorithms
On the Asymptotic Behavior of Multirecombinant Evolution Strategies
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Hi-index | 0.00 |
In this paper, a new algorithm of Gene Intrusion on a Society of Hill-Climbers (GI-SoHC) is introduced. In GI-SoHC, the genes which contribute most to the best fitness of the best climber in each generation are selected and inserted to other climbers for replacing their own genes, such that the society can have faster climbing speed and better climbing locations.The experiment results show that with Gene Intrusion, climbers generally and averagely perform better in that they climb more quickly than the original Historical Society of Hill-Climbers, especially in the early stage of the climbing process.