Method for configuring a driver assistance apparatus of a motor vehicle, which driver assistance apparatus has a neural selection network for selecting a vehicle function (a t) of the motor vehicle to be performed, having the method steps of: a) capture of surroundings of the motor vehicle at a first time (t) and provision of first surroundings information (s t), which represents the surroundings captured at the first time (t), by a surroundings capture device of the motor vehicle; b) selection, by the neural selection network, on the basis of the provided first surroundings information (s t), of at least one vehicle function (a t) to be performed; c) prediction of a consequence of performance of the selected vehicle function (a t) on the basis of the first surroundings information (s t) by a neural recurrent prediction network of the driver assistance apparatus, wherein the consequence predicted on the basis of the first surroundings information (s t) is second surroundings information (s t+1), which represents the surroundings of the motor vehicle at a second time (t+1) that follows the first time (t), on the basis of the selected vehicle function (a t) on the assumption that the selected vehicle function (a t) is performed before the second time (t+1); d) provision of information determined by the predicted consequence to the neural selection network, wherein the information provided to the neural selection network is the predicted second surroundings information (s t+1) and a reward value (r t) predefined, according to a rule stored in the driver assistance apparatus, for a combination of the first surroundings information (s t) and the selected vehicle function (a t) to be performed; e) adaptation of the neural selection network by means of reinforcement learning on the basis of the provided information, i.e. on the basis of the reward value (r t) and the second surroundings information (s t+1). a) capture of surroundings of the motor vehicle at a first time (t) and provision of first surroundings information (s t), which represents the surroundings captured at the first time (t), by a surroundings capture device of the motor vehicle; b) selection, by the neural selection network, on the basis of the provided first surroundings information (s t), of at least one vehicle function (a t) to be performed; c) prediction of a consequence of performance of the selected vehicle function (a t) on the basis of the first surroundings information (s t) by a neural recurrent prediction network of the driver assistance apparatus, wherein the consequence predicted on the basis of the first surroundings information (s t) is second surroundings information (s t+1), which represents the surroundings of the motor vehicle at a second time (t+1) that follows the first time (t), on the basis of the selected vehicle function (a t) on the assumption that the selected vehicle function (a t) is performed before the second time (t+1); d) provision of information determined by the predicted consequence to the neural selection network, wherein the information provided to the neural selection network is the predicted second surroundings information (s t+1) and a reward value (r t) predefined, according to a rule stored in the driver assistance apparatus, for a combination of the first surroundings information (s t) and the selected vehicle function (a t) to be performed; e) adaptation of the neural selection network by means of reinforcement learning on the basis of the provided information, i.e. on the basis of the reward value (r t) and the second surroundings information (s t+1).