Stochastic approximation of the extremum point of the optimality criterion of complex systems

An adaptive stochastic approximation algorithm is discussed. Algorithm efficiency is estimated at a finite size of the sample. Comparison in terms of search costs is made for stochastic approximation algorithms differing in methods for computation of the random functional gradient.