%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