Criterial algorithms of stochastic optimization

The paper is concerned with criterial optimization problems where it is necessary to estimate the optimal value of the performance criterion while the coordinates of the extremum point are unimportant. The proposed algorithms solve criterial problems in the presence of random errors in measurements of the gradient and provide an optimal criterial rate of convergence.