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Two soft computing paradigms for automated learning control of complex systems are briefly de scribed. To illustrate the utility of the paradigms, they are applied to a desalination process and sim ulations are performed. The first paradigm in corporates Genetic Algorithms (GA) in a learn ing scheme to adapt parameters of the fuzzy controller to changing environmental conditions. The second paradigm concentrates on a methodology which uses a Neural Network (NN) to adapt a fuzzy logic controller. Simulation results of fuzzy controllers learned with the aid of these soft computing paradigms are presented.