@inproceedings {pub3955,
	title = {Simultaneous Interactive Learning of Identities and Attributes of Objects in an Autonomous Mobile Robot{\textquoteright}s Environment},
	author = {Jennifer Kreger AND Stephan Hasler AND Ute Bauer-Wersing},
	year = {2019},
	month = {July},
	abstract = {In the extended abstract we describe our system of autonomous robots cooperating with humans. The robots provide tasks concerning different objects in the environment (e.g. bringing them somewhere), thus they must be able to communicate with the user about them. Hence, the robots have to recognize identities of objects, but also handle unknown objects by describing them with their attributes or understanding attribute-based descriptions of these objects. To do so, they must keep track of the objects in the environment autonomously and take care that they know how to refer to them appropriately. We propose a three staged machine learning system that uses CNN features and label tags given by the human user to simultaneously learn the identity of objects and their attributes. With these, it can describe known and unknown objects, and formulate requests to gather missing information.},
	publisher = {Frankfurt Institute for Advanced Studies (FIAS) in Frankfurt (Germany)},
	booktitle = {Fourth International Workshop on Intrinsically-Motivated Open-ended Development (IMOL2019)}
}