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Adaptive policies for discrete-time stochastic control systems with unknown disturbance distribution. (English) Zbl 0637.93075

Discrete-time stochastic control systems are considered. The disturbance or driving process is a sequence of independent and identically distributed (i.i.d.) random elements whose common distribution is unknown. The state is completely observable together with realizations of the driving process. Adaptive control policies for the problem of maximizing the discounted reward criterion are introduced and studied. These policies are asymptotically optimal and for each of them uniform approximations of the optimal reward function can be obtained.
Reviewer: V.Zhukovin

MSC:

93E20 Optimal stochastic control
93C40 Adaptive control/observation systems
93C55 Discrete-time control/observation systems
60E99 Distribution theory
93C10 Nonlinear systems in control theory
93E10 Estimation and detection in stochastic control theory
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