Evolutionary optimisation of evolving connectionist systems
Michael John Watts, Nikola Kirilov Kasabov · 2003
The paper presents a method for optimising parameter values of evolving connectionist systems (ECoS) for life-long learning. The method is based on evolutionary computation principles, and on genetic algorithms in particular. The method is illustrated on a spoken phoneme data classification task.