Robot Likeability and Reciprocity in Human Robot Interaction: Using Ultimatum Game to determinate Reciprocal Likeable Robot Strategies
Tóm tắt
Among of the factors that affect likeability, reciprocal response towards the other party is one of the multiple variables involved in social interaction. However, in HRI, likeability is constrained to robot behavior, since mass-produced robots will have identical physical embodiment. A reciprocal robot response is desirable in order to design robots as likeable agents for humans. In this paper, we discuss how perceived likeability in robots is a crucial multi-factorial phenomenon that has a strong influence on interactions based on reciprocal robot decisions. Our general research question is: What type of reciprocal robot behavior is perceived as likeable for humans when the robot’s decisions affect them? We designed a between/within
$$2 \times 2 \times 2$$
experiment in which the participant plays our novel Alternated Repeated Ultimatum Game (ARUG) for 20 rounds. The robot used in the experiment is an NAO robot using four different reciprocal strategies. Our results suggest that participants tend to reciprocate more towards the robot who starts the game and using the pure reciprocal strategy compared with other combined strategies (Tit for Tat, Inverse Tit for Tat and Reciprocal Offer and Inverse Reciprocal Offer). These results confirm that the Norm of the Reciprocity applies in HRI when participants play ARUG with social robots. However, the human reciprocal response also depends on the profits gained in the game and who starts the interaction. Similarly, the likeability score is affected by robot strategies such as reciprocal (Robot A) and generous (Robot C). and there are some discrepancies in the likeability score between the reciprocal robot and the generous robot behavior.
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