Immunized Computational Systems combine a priori knowledge with the adapting capabilities of immune systems to provide a powerful alternative to currently available techniques for intelligent control. In this paper, we present a perspective on various levels of intelligent control and relate them to similar functioning in human immune systems. A technique for implementing immunized computational systems as adaptive critics is presented and the technique is then applied to a simple two degree-of-freedom control problem as well as a more complex flight path generator for level 2, non-linear, full-envelope, intelligent aircraft control.
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