Six Necessary Qualities of Self-learning Systems - A Short Brainstorming

In this position paper the broad issue of learning and self-organisation is addressed. I deal with the question how biological and technological information processing systems can autonomously acquire cognitive capabilities only from data available in the environment. In the main part I claim six qualities that are, in my opinion, necessary qualities of self-learning systems. These qualities are (1) hierarchical processing, (2) emergence on all levels of hierarchy, (3) multi-directional information transfer between the levels of hierarchy, (4) generalization from few examples, (5) exploration, and (6) adaptivity. I try to support my considerations by theoretical reflections as well as by an informal introduction of a self-learning system that features these qualities and displays promising behavior in object recognition applications. Although this paper has more the character of a brainstorming the proposed qualities can be regarded as roadmap for problems to be addressed in future research in the field of autonomous learning.