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A heuristic search is described which has the aim of finding practically all the extrema of a given nonlinear functional. A standard unimodal descent algorithm is employed for finding individual extrema. This basic algorithm is applied repeatedly using various computed initial points and starting directions. Through the additional use of several learning cycles most of the available extrema can be found. Numerical experiments indicate that the method is very efficient for the functionals of dimensions 15-20 with 20-25 extrema.