Computer-implemented method for training a machine learning system for generating driving profiles, in particular speed profiles, profiles of accelerator pedal positions or profiles of a gear ratio, of a vehicle, characterized by the steps of: - first journey routes being selected from a first database containing journey routes, - a generator of the machine learning system obtaining the first journey routes as input variables and generating associated first driving profiles each relating to the first journey routes, - journey routes and respectively associated driving profiles recorded in driving mode being stored in a second database, - second journey routes and also respectively associated second driving profiles recorded in driving mode being selected from the second database, - a discriminator of the machine learning system obtaining as input variables pairs made up of one of the first journey routes with a respectively associated first, generated driving profile and pairs made up of second journey routes with a respectively associated second driving profile recorded in driving mode, - the discriminator calculating, as a function of the input variables, outputs which characterize for each pair, obtained as input variables, whether the pair is a pair with a first, generated driving profile or a pair with a second driving profile recorded in driving mode, - a target function being optimized as a function of the outputs of the discriminator, the target function representing a distance between the distribution of the pairs with first, generated driving profiles and the distribution of the pairs with second driving profiles recorded in driving mode, wherein parameters of the machine learning system are adapted as a function of the optimization of the target function in such a way that - the discriminator is optimized for distinguishing between the first, generated driving profiles and the second driving profiles recorded in driving mode, - the generator is optimized for generating first, generated driving profiles in a first distribution, it being extremely difficult for the discriminator to distinguish the first, generated driving profiles from second driving profiles recorded in driving mode which are present in a second distribution. - first journey routes being selected from a first database containing journey routes, - a generator of the machine learning system obtaining the first journey routes as input variables and generating associated first driving profiles each relating to the first journey routes, - journey routes and respectively associated driving profiles recorded in driving mode being stored in a second database, - second journey routes and also respectively associated second driving profiles recorded in driving mode being selected from the second database, - a discriminator of the machine learning system obtaining as input variables pairs made up of one of the first journey routes with a respectively associated first, generated driving profile and pairs made up of second journey routes with a respectively associated second driving profile recorded in driving mode, - the discriminator calculating, as a function of the input variables, outputs which characterize for each pair, obtained as input variables, whether the pair is a pair with a first, generated driving profile or a pair with a second driving profile recorded in driving mode, - a target function being optimized as a function of the outputs of the discriminator, the target function representing a distance between the distribution of the pairs with first, generated driving profiles and the distribution of the pairs with second driving profiles recorded in driving mode, wherein parameters of the machine learning system are adapted as a function of the optimization of the target function in such a way that - the discriminator is optimized for distinguishing between the first, generated driving profiles and the second driving profiles recorded in driving mode, - the generator is optimized for generating first, generated driving profiles in a first distribution, it being extremely difficult for the discriminator to distinguish the first, generated driving profiles from second driving profiles recorded in driving mode which are present in a second distribution.