Groups of humans and robots: Understanding membership preferences and team formation

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Abstract

Although groups of robots are expected to interact with groups of humans in the near future, research related to teams of humans and robots still appears scarce. This paper contributes to the study of human-robot teams by investigating how humans choose robots to partner with in a multi-party game context. The novelty of our work concerns the successful design and development of two social robots that are able to autonomously interact with a group of two humans in the execution of a social and entertaining task. The development of these two characters was motivated by psychological research on learning goal theory, according to which we interpret and approach a given task differently depending on our learning goal (oriented more towards either relationship building or competition). Thus, we developed two robotic characters implemented in two robots: Emys (competitive robot) and Glin (relationship-driven robot). In our study, a group of four (two humans and two autonomous robots) engaged in a social and entertaining card game. Our study yields several important conclusions regarding groups of humans and robots. (1) When a partner is chosen without previous partnering experience, people tend to prefer robots with relationship-driven characteristics as their partners compared with competitive robots. (2) After some partnering experience has been gained, the choice becomes less clear and additional driving factors emerge: (2a) participants with higher levels of competitiveness (personal characteristics) tend to prefer Emys, whereas those with lower levels prefer Glin, and (2b) the choice of which robot to partner with also depends on team performance, with the winning team being the preferred choice.

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APA

Correia, F., Petisca, S., Alves-Oliveira, P., Ribeiro, T., Melo, F. S., & Paiva, A. (2017). Groups of humans and robots: Understanding membership preferences and team formation. In Robotics: Science and Systems (Vol. 13). MIT Press Journals. https://doi.org/10.15607/rss.2017.xiii.024

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