%A Yuval Marom
%A Gillian Haynes
%T Influencing Robot Learning Through Design and Social Interactions: A Balancing Framework
%X 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.
%K innate knowledge, acquired knowledge, nature-nurture trade-off, development and ineraction
%P 75-82
%E Luc Berthouze
%E Hideki Kozima
%E Christopher G. Prince
%E Giulio Sandini
%E Georgi Stojanov
%E Giorgio Metta
%E Christian Balkenius
%V 117
%D 2004
%I Lund University Cognitive Studies
%L cogprints4072

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