A new approach to the feature detection problem, i.e. learning "useful" primitive features from raw images, is proposed. The "useful" features are defined within the training environment as those that allow the learning agent (learning system) to form object representations sufficient for subsequent object recognition. In other words, the "useful" features detected are discriminating, useful features.