An integrated system for interactive continuous learning of categorical knowledge

Skočaj, Danijel, Vrečko, Alen, Mahnič, Marko , Janíček, Miroslav, Kruijff, Geert-Jan M, Hanheide, Marc, Hawes, Nick, Wyatt, Jeremy L, Keller, Thomas, Zhou, Kai, Zillich, Michael and Kristan, Matej (2016) An integrated system for interactive continuous learning of categorical knowledge. Journal of Experimental & Theoretical Artificial Intelligence, 28 (5). pp. 823-848. ISSN 0952-813X


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This article presents an integrated robot system capable of interactive learning in dialogue with a human. Such a system needs to have several competencies and must be able to process different types of representations. In this article, we describe a collection of mechanisms that enable integration of heterogeneous competencies in a principled way. Central to our design is the creation of beliefs from visual and linguistic information, and the use of these beliefs for planning system behaviour to satisfy internal drives. The system is able to detect gaps in its knowledge and to plan and execute actions that provide information needed to fill these gaps. We propose a hierarchy of mechanisms which are capable of engaging in different kinds of learning interactions, e.g. those initiated by a tutor or by the system itself. We present the theory these mechanisms are build upon and an instantiation of this theory in the form of an integrated robot system. We demonstrate the operation of the system in the case of learning conceptual models of objects and their visual properties.

Keywords:Cognitive system, interactive learning, motive management, knowledge gap detection, extrospection, introspection, NotOAChecked
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
G Mathematical and Computer Sciences > G440 Human-computer Interaction
H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G760 Machine Learning
Divisions:College of Science > School of Computer Science
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ID Code:22203
Deposited On:05 Feb 2016 21:39

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