BMBF Verbundprojekt - OML: Organisches Maschinelles Lernen(FKZ01IS18040B)
The goal of the project "Organic Machine Learning" (OML) is to break the conventional, rigid approach of training an deploying of machine learning systems and to develop methods for machine learning which resemble organic learning, especially human learning, where systems learn throughout their entire lifetime - especially during application.
The way of learning shall become more organic. Instead of learning on very large, clean and well-structured training data, which have been prepared in a time-consuming manner, the systems developed in OML shall learn from heterogeneous data with little or no preparation, like they occur in real world scenarios, and shall require less training data, like humans do. Different sources, such as interaction with humans and own experience, shall be combined in a multimodal way and learning shall be focused on cases of uncertainty. To achieve this, systems must be able to detect in which cases they are unsure and where further learning is necessary. Furthermore, learning systems should not be a »black box« whose functioning outsiders cannot see into. Instead, they should be able to explain their decision-making and behavior. With the ability to justify their decisions, those system will become more accepted by humans and their application in real world environments possible.
Finally, the developed system shall be integrated in a robotic system. In an interactive robot programming scenario, the robot shall learn new skills from scratch by learning from physical, visual and verbal interaction with a human as well as own experience - just how an apprentice is taught by his master.
Weitere Informationen: http://www.oml-project.org/
Ansprechpartner: Burgard W
Autonome intelligente Systeme
Prof. Dr. Wolfram Burgard
Georges-Köhler-Allee Geb. 080
79110 Freiburg im Breisgau
Telefon: +49 (761) 203-8026
Fax: +49 (761) 203-8007
Karlsruher Institut für Technologie