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 ). <EOS>