Algorithmic Learning: Formal models and prototypical applications

Abstract

The vision of assistance systems is to use machines not merely as tools but as intelligent assistants with which humans can solve their tasks cooperatively. The approach considered below is to enhance the required machine-human interaction by machine learning strategies. In order to enable an analytical study of the relevant general learning tasks and techniques, different formal learning models are compared and related to one another. The capabilities of the corresponding learning algorithms are illustrated and discussed within the framework of prototypical applications.