Abstract
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.
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Klüver, C., Klüver, J. (2013). Self-organized Learning by Self-Enforcing Networks. In: Rojas, I., Joya, G., Gabestany, J. (eds) Advances in Computational Intelligence. IWANN 2013. Lecture Notes in Computer Science, vol 7902. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38679-4_52
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DOI: https://doi.org/10.1007/978-3-642-38679-4_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38678-7
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