In many areas, neural networks have achieved a performance comparable to or better than that of humans. However, neural networks usually learn in a different way than humans. The neuronal networks are trained with gigantic data sets and after learning these data sets they are used in production. Humans learn continuously from their interaction with their environment. In organic machine learning, neural networks should learn in the same way as humans.
In this seminar, current research results on different aspects of such organic learning
neural networks are presented. Possible topics are Reinforcement Learning, integration of knowledge,
learning concepts, feedback mechanisms, ...