Abstract
As personal robots enter the social environments of our workplaces and homes, it will be important for them to be able to learn from a wide demographic of people. Our research seeks to identify simple, natural, and prevalent human teaching cues that are useful for directing the attention of robot learners so that robots can learn efficiently and effectively from these interactions.
This research goal is significant for several reasons. First, most people do not have expertise in robotics or machine learning techniques. Second, personal robots will have to learn new tasks and skills within the bounds of human attention and patience. Third, people bring a lifetime of experience in learning from and teaching others and naturally do quite a lot to socially structure appropriate learning environments and interactions so that others can learn efficiently and effectively. Personal robots should be able to leverage these social interactions to also learn efficiently and effectively from people.
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Breazeal, C., Berlin, M., Gray, J., Chao, C. (2009). Teaching Robots via Natural Nonverbal Cues. In: Khatib, O., Kumar, V., Pappas, G.J. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00196-3_25
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DOI: https://doi.org/10.1007/978-3-642-00196-3_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00195-6
Online ISBN: 978-3-642-00196-3
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