ISO-learning approximates a solution to the inverse-controller problem in an unsupervised behavioural paradigm

In the previous article we have introduced an isotropic algorithm for temporal sequence learning (ISO-learning). Here we embed this algorithm into a formal nonevaluating (“teacher-free”) environment which establishes a sensor-motor feedback. The system is initially guided by a fixed reflex reaction which has the objective disadvantage that it can only react after a disturbance has occurred. ISO-learning eliminates this disadvantage by replacing the reflex-loop reactions with earlier anticipatory actions. In this article we will analytically demonstrate that this process can be understood in terms of control theory showing that the system learns the inverse controller of its own reflex. Thereby this system is able to learn a simple form feed-forward motor control.