Self-organized Learning by Self-Enforcing Networks

We describe a new type of self-organized learning neural networks, namely the Self-Enforcing Network SEN. After introducing our theoretical and methodical frame, basically orientated to the theory of Piaget, we show the logical principles of SEN, including a new activation function, a new learning rule, and a specific visualization algorithm. The operations of SEN are demonstrated with the examples of assimilating new perceptions of animals, the application of a SEN to direct marketing, and the usage of a SEN as consulting system for pupils and beginners at the university. Apparently SEN can be used in many different contexts.