1. A method for computer-aided control of a technical system, comprising: characterizing a dynamic behavior of the technical system for a plurality of time points by a state of the technical system and an action carried out on the technical system for each time point, wherein an action at a time point results in a sequential state of the technical system at a next time point; learning an action selection rule with a plurality of data records, wherein each data record comprises the state of the technical system at the time point, the action carried out in the state and the sequential state, and wherein an evaluation is assigned to each data record, the learning of the action selection rule comprising: modeling of a quality function by a first neural network comprising the states and actions of the technical system as parameters; learning the first neural network based on an optimality criterion, which is a function of the evaluations of the data records and the quality function, an optimum action in respect of the quality function being modeled by a second neural network, which is learned based on the quality function; and controlling the technical system such that the actions to be carried out on the technical system are selected using the action selection rule based upon the second neural network.