This paper describes a social robotic game player that is able to successfully play a team card game called Sueca. The question we will address in this paper is: how can we build a social robot player that is able to balance its ability to play the card game with natural and social behaviours towards its partner and its opponents. The first challenge we faced concerned the development of a competent artificial player for a hidden information game, whose time constraint is the average human decision time. To accomplish this requirement, the Perfect Information Monte Carlo (PIMC) algorithm was used. Further, we have performed an analysis of this algorithm's possible parametrizations for games trees that cannot be fully explored in a reasonable amount of time with a MinMax search. Additionally, given the nature of the Sueca game, such robotic player must master the social interactions both as a partner and as an opponent. To do that, an emotional agent framework (FAtiMA) was used to build the emotional and social behaviours of the robot. At each moment, the robot not only plays competitively but also appraises the situation and responds emotionally in a natural manner. To test the approach, we conducted a user study and compared the levels of trust participants attributed to the robots and to human partners. Results have shown that the robot team exhibited a winning rate of 60%. Concerning the social aspects, the results also showed that human players increased their trust in the robot as their game partners (similar to the way to the trust levels change towards human partners).

Emotions are a key element in all human interactions. It is well documented that individual- and group-level interactions have different emotional expressions and humans are by nature extremely competent in perceiving, adapting and reacting to them. However, when developing social robots, emotions are not so easy to cope with. In this paper we introduce the concept of emotional climate applied to human-robot interaction (HRI) to define a group-level emotional expression at a given time. By doing so, we move one step further in developing a new tool that deals with group emotions within HRI.