Abstract: A computer system obtains an image or video of a person, such as a shopper. The image or video includes the face of the person. The system extracts low level features from the image or video. The low level features may be Gabor features. The system examines the low level features to designate stimuli that are likely to result in preferred behaviors associated with the person. The system analyzes the plurality of designated stimuli based on predetermined criteria to select one or more selected stimuli, and then causes the selected stimuli to be rendered to the person. The predetermined criteria may be economic criteria, such as a requirement to select the stimulus with the highest expected economic benefit from among the various designated stimuli.

Abstract: Machine learning systems are represented as directed acyclic graphs, where the nodes represent functional modules in the system and edges represent input/output relations between the functional modules. A machine learning environment can then be created to facilitate the training and operation of these machine learning systems.