Proxy Cyber aims to create a reactive system that uses ambient artificial intelligence to both teach and learn from the subjects participating in testing the many applications of Brain Computer Interface.The ambient intelligence system includes biological applications (neural prosthetics) to measure in real-time the internal states of the user/consumer both toward and away from the AI.These states include motivation, affective states and reactiveness. The task is to maintain these states – if the user loses his motivation or interest, the system will react by changing its behaviour in order to make the system interesting again. Or if the user is very motivated and highly concentrated the system can provide more subtle controls.The system controls the level of control based on the states of the user.

At the core of Proxy Cybernetics ,an artificial intelligent learns relationships between the data induction (hearing,seeing ,deep learning) upon the user and their environment.The intelligent layer adapts the behavior of the Tele-Presence from data gathered from the users manipulations of the AI parameters, as well as additional data about the environment and the psychological state of the user. Each contributing ambient agent has a machine-learning model for predicting the subject's state from interfaced data based on thought ,emotion and reaction to their virtual and non -virtual environment. On a system wide scale the data can be divided into input- output data (agent states) and input-only data (user and the environment).The learning weights of the concurrent data samples are determined by an engagement variable derived from the user model.

Condition based algorithms are not limited to machine-learning ,all aspects of the Proxy 's life are manipulated so 'change agents' in the field of behavioral testing can understand input that effect the states of the user.