Abstract
As intelligent robots become integrated into society, it becomes important for them to be capable of natural, human-like human-robot interaction (HRI). While there has been some progress on enabling natural-language based HRI (Mavridis, 2015), most natural language enabled robots rely on highly scripted interactions, keyword spotting, and shallow natural language processing techniques. For many applications, these methods may be sufficient to achieve the desired behavior, which may be restricted to a small class of tasks. Such methods, however, are not helpful for the development of robots that are generally and flexibly taskable, that can learn about new entities and concepts on the fly, and that are capable of engaging in truly natural human-like HRI.
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