Curiosity did not kill the robot: a curiosity-based learning system for a shopkeeper robot

Malcolm Doering, Phoebe Liu, Dylan F. Glas, Takayuki Kanda, Dana Kulic, Hiroshi Ishiguro

Research output: Contribution to journalArticleResearchpeer-review


Learning from human interaction data is a promising approach for developing robot interaction logic, but behaviors learned only from offline data simply represent the most frequent interaction patterns in the training data, without any adaptation for individual differences. We developed a robot that incorporates both data-driven and interactive learning. Our robot first learns high-level dialog and spatial behavior patterns from offline examples of human--human interaction. Then, during live interactions, it chooses among appropriate actions according to its curiosity about the customer's expected behavior, continually updating its predictive model to learn and adapt to each individual. In a user study, we found that participants thought the curious robot was significantly more humanlike with respect to repetitiveness and diversity of behavior, more interesting, and better overall in comparison to a non-curious robot.
Original languageEnglish
Article number15
Number of pages24
JournalACM Transactions on Human-Robot Interaction
Issue number3
Publication statusPublished - Aug 2019
Externally publishedYes

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