Evolutionary system identification and control

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.<
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