The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
Design Rules: The Power of Modularity Volume 1
Design Rules: The Power of Modularity Volume 1
Modeling Building-Block Interdependency
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
On the complexity of hierarchical problem solving
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Variable discrimination of crossover versus mutation using parameterized modular structure
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A building-block royal road where crossover is provably essential
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Evolutionary transitions as a metaphor for evolutionary optimisation
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Symbiosis enables the evolution of rare complexes in structured environments
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part II
Symbiogenesis as a mechanism for building complex adaptive systems: a review
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
| Hi-index | 0.00 |
Symbiosis, the collaboration of multiple organisms from different species, is common in nature. A related phenomenon, symbiogenesis, the creation of new species through the genetic integration of symbionts, is a powerful alternative to crossover as a variation operator in evolutionary algorithms. It has inspired several previous models that use the repeated composition of preadapted entities. In this paper we introduce a new algorithm utilizing this concept of symbiosis which is simpler and has a more natural interpretation when compared with previous algorithms. In addition it achieves success on a broader class of modular problems than some prior methods.