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Influencing Robot Learning Through Design and Social Interactions: A Balancing Framework

By Yuval Marom and Gillian Haynes

Abstract

We present a framework for addressing a challenging trade-off between influencing the learning of a robot through design and through social interactions. We identify different kinds of influences that a designer can introduce at design time, and that an expert can introduce using social interactions, and we use these to characterise a two-dimensional design space. As well as discussing how the two sources of influence affect each other, we propose how learning performance typically varies as a result, and present some empirical findings

Topics: Machine Learning, Artificial Intelligence, Robotics
Publisher: Lund University Cognitive Studies
Year: 2004
OAI identifier: oai:cogprints.org:4072

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