  The development of the works of the author about adaptive algorithms of
teaching the robotic systems with the help of operator is described here. An
operator is assumed to be an experience decision-maker and sane carrier of a
target which the robotic system needs to achieve. The works characteristic is
that the behavior of the robotic system is not specified a priori (as standard)
but is formed adaptively based on the information about the situation and
decisions made by a decision-maker. In this scheme the robotic system and the
decision-maker can cooperate in the normal operation mode of the robotic system
or in the time sharing mode with the possibility to plan actively the
experiment on the robotic system. If the adaptive scheme is chosen, there are
teaching stages and operating stages of the robotic system. At that the
decision-maker can act slowly having the possibility to weigh the decision
made. This way allows the robotic system reacting flexibly by switching between
preset models and respond to the environment instability. The data integrity
about the environment condition and about target preferences of an operator
plays a very important role in robotic system work. The effective work of the
robotic system depends on the effective settings of a preference model of the
robotic system based on the decisions of the decision-maker and on the
effective control. The influence of settings and control factors on the index
of effectiveness of the robotic system is subject of this work. The uncertainty
may be caused by the data flow limitation received by the operator on the stage
of the model setting.
