Evolutionary algorithms (EAs) are inspired by the biological model of evolution and natural selection. In the natural world, evolution helps species adapt to their environments. Evolutionary algorithms are based on a simplified model of this biological evolution. To solve a particular problem we create an environment in which potential solutions can evolve. The environment is shaped by the parameters of the problem and encourages the evolution of good
Evolutionary algorithms (EAs) are inspired by the biological model of evolution and natural selection. In the natural world, evolution helps species adapt to their environments. Evolutionary algorithms are based on a simplified model of this biological evolution. To solve a particular problem we create an environment in which potential solutions can evolve. The environment is shaped by the parameters of the problem and encourages the evolution of good solutions.
The field of Evolutionary Computation encompasses several types of evolutionary algorithm. These include Genetic Algorithms (GAs), Evolution Strategies, Genetic Programming (GP), Evolutionary Programming and Learning Classifier Systems.