Algorithmic models of human behavior following Yu. E. Nesterov

Given research considers several convex stochastic optimization problems. These problems are solved using the methods that are very similar to the possible people behavior. The presentation is based mainly on the consideration the online stochastic version of the mirror descent method. Novelty is made up by the fact that almost all the scenarios are considered in the case of noise, including those of nonrandom nature. One of the goals of this preprint is to answer to the questions raised during the final lecture of the series of lectures read by Yu.E. Nesterov in April 2016 in the HSE (Moscow) (https://www.youtube.com/user/PreMoLab).