Robust pseudogradient adaptation algorithms

A recurrence algorithm is proposed for finding the unconditional extremum of a function with random noises in computing its gradient without a need to know precisely the noise distribution lae. The algorithm is proved to be optimal in the asymptotically minimax sense for this kind of noise. Relation with robust procedures in statistics is discussed.