Design of SLAYR Neural Networks Using Evolutionary Programming

This paper describes the use of evolutionary programming for computer-aided design and testing of neural single layer regulators. The design and testing problem is viewed as a game in that the controller parameters are to be chosen with a minimax criterion, i.e. to minimize the loss associated with their use on the worst possible plant parameters. The technique permits analysis of neural strategies against a set of plants. This gives both the best choice of control parameters and identification of the plant configuration which is most difficult for the best controller to handle. Computations of an approximate minimax solution are fast, requiring less than 24 hours in background mode on a SUN 4/260 running with other normal traffic.

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