1. Method for controlling a processing operation of a workpiece by means of a Reinforcement Learning (RL) agent unit, comprising the steps of: (a) observing an interaction zone in the workpiece by means of at least one radiation sensor to generate at least one sensor signal s t ; wherein the workpiece is processed using an actuator having an initial actuator value a t ; (b) determining a basis function φ(s t ) from the set of sensor signals s t ; (c) determining a reward function r t giving the probability of good results of the processing operation; (d) choosing a next actuator value a t+1 on the basis of a policy π depending on the reward function r t and the basis function φ(s t ); and (e) repeating the steps (a) to (d) for further time points to perform an R L controlled processing operation, and wherein steps (a) and (b) comprise the steps of: recording a pixel image at an initial time point of an interaction zone in the workpiece by means of a camera, wherein the workpiece is processed using an actuator having an initial actuator value a t ; converting the pixel image into a pixel vector s t ; and representing the pixel vector s t by a sum of predetermined pixel mappings each multiplied by a corresponding feature value, wherein the set of feature values φ(s t ) represents the basis function φ(s t ).