Showing papers on "Evolutionary computation published in 1990"
27 Nov 1990
TL;DR: Evolutionary optimization is proposed as a method for machine learning that can address systems in which there is little or no prior knowledge and is more versatile than classic prediction and correlation error methods.
Abstract: Evolutionary optimization is proposed as a method for machine learning. Simulating evolution can be used for the prediction, identification, and control of time-varying plants. Models which describe the input-output characteristics of the system are evolved in fast time. This evolutionary programming can address systems in which there is little or no prior knowledge. There is no requirement for using a squared error or other smooth criterion. The technique is more versatile than classic prediction and correlation error methods. >
4 citations