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Klüver, C., & Klüver, J. (2013). Self-Organized Learning by Self-Enforcing Networks. In I. Rojas, G. Joya, & J. Cabestany (Eds.), Proceedings of the 12th International Work-Conference on Artificial Neural Networks (IWANN 2012), Part I. Lecture Notes in Computer Science, Vol. 7902, Springer, Berlin, Heidelberg, 518-529.
https://doi.org/10.1007/978-3-642-38679-4_52

has been cited by the following article:

• TITLE: Paradoxes, Self-Referentiality, and Hybrid Systems: A Constructive Approach

  AUTHORS: Jürgen Klüver

  KEYWORDS: Logic, Paradoxes, Self-Referentiality, Hybrid Computer Programs

  JOURNAL NAME: Open Journal of Philosophy, Vol.7 No.1, January 24, 2017

  ABSTRACT: Since the discovery of the paradoxes of self-referentiality or self-reference respectively logicians and mathematicians tried to avoid self-reference when constructing formal systems. Yet “real” complex systems like the mind are characterized by self-reference and can accordingly only be modeled by formal systems that are also basically self-referential. In this article I show that and how self-referential computer programs, understood as algorithmic formal systems, are not only possible but also since some time quite common in special branches of computer science. Examples for this argument are neural networks and so-called hybrid systems, i.e. combination of different sub systems. The hybrid system SOCAIN, a combination of a cellular automaton, a neural network and a genetic algorithm is an example for the fruitfulness of using self-reference in a systematic way. In particular, such systems consist of mutually dependent sub systems, i.e. form no static hierarchy.