Models and methods of identification and adaptive stochastic control under uncertainty

The topic is a model of stochastic optimal control with Markovian base, which is determined by a set of objects. If certain states are accessible for direct observation, the problem of dynamic decision making in conditions of the type of risk outlet created by accidenting of states takes place. Under given conditions, game ideology and constructive methods of successive identification and adaptive decision-making are developing. The best decisions are understood in the sense of dynamic balances of Shtakelberg. Together the described results realize system methodology of decision-making. It permits to investigate problem of decision-making not in particular suppositions of concrete tasks but as a common problem for sufficiently broad class of operated systems marked by appropriate postulates and bases. That opens possibility to describe and solve problems which could not be solved before.