Learning to Interact with the Caretaker: A Developmental Approach

Authors:
Antoine Hiolle;Lola Cañamero;Arnaud J. Blanchard
Affiliations:
Adaptive Systems Research Group, School of Computer Science, University of Hertfordshire, College Lane, Hatfield, Herts AL10 9AB, UK;Adaptive Systems Research Group, School of Computer Science, University of Hertfordshire, College Lane, Hatfield, Herts AL10 9AB, UK;Adaptive Systems Research Group, School of Computer Science, University of Hertfordshire, College Lane, Hatfield, Herts AL10 9AB, UK
Venue:
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Year:
2007

Citing 2
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Abstract

To build autonomous robots able to live and interact with humans in a real-world dynamic and uncertain environment, the design of architectures permitting robots to develop attachment bonds to humans and use them to build their own model of the world is a promising avenue, not only to improve human-robot interaction and adaptation to the environment, but also as a way to develop further cognitive and emotional capabilities. In this paper we present a neural architecture to enable a robot to develop an attachment bond with a person or an object, and to discover the correct sensorimotor associations to maintain a desired affective state of well-being using a minimum amount of prior knowledge about the possible interactions with this object.