Learning to Learn New Models of Human Activities in Indoor Settings
Biological cognitive systems have the great capability to recognize and interpret unknown situations. Equally, they can integrate new observations easily within their existing knowledge base. Autonomous artificial agents to a large extent still lack such capacities. In this paper, we work towards this direction, as we do not only detect abnormal situations, but are also able to learn new concepts during runtime.