An Accelerated Genetic Algorithm
作者:John R. Podlena, Tim Hendtlass
摘要
The standard Genetic Algorithm, originally inspired by natural evolution, has displayed its effectiveness in solving a wide variety of complex problems. This paper describes the use of the natural phenomenon known as the Baldwin effect (or cross-generational learning) as an enhancement to the standard Genetic Algorithm. This is implemented by using an artificial neural network to store aspects of the population's history. It also describes a method by which the negative side effects of a large elite sub-population can be counter-balanced by using an ageing coefficient in the fitness calculation.
论文关键词:genetic algorithm, neural networks, Baldwin effect, optimisation, history
论文评审过程:
论文官网地址:https://doi.org/10.1023/A:1008227606285