The social element of playing games is what makes us play together to enjoy more than just what the game itself has to offer. There are millions of games with different rules and goals; They are played by people of many cultures and various ages. However, this social element remains as crucial. Nowadays, the role of social robots and virtual agents is rapidly expanding in daily activities and entertainment and one of these areas is games. Therefore, it seems desirable for an agent to be able to play games socially, as opposed to simply having the computer make the moves in game application. To achieve this goal, verbal and non-verbal communication should be inspired by the game events and human input, to create a human-like social experience. Moreover, a better social interaction can be created if the agent can change its game strategies in accordance with social criteria. To bring sociability to the gaming experience with many different robots, virtual agents and games, we have developed a generic software framework which generates social comments based on the gameplay semantics. We also conducted a user study, with this framework as a core component, involving the rummy card game and the checkers board game. In our analysis, we observed both subjective and objective measures of the effects of social gaze and comments in the gaming interactions. Participants' gaming experience proved to be significantly more social, human-like, enjoyable and adoptable when social behaviors were employed. Moreover, since facial expressions can be a strong indication of internal state, we measured the number of participants' smiles during the gameplay and observed them to smile significantly more when social behaviors were involved than when they were not.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1199 |
| Date | 10 April 2014 |
| Creators | Behrooz, Morteza |
| Contributors | Craig E. Wills, Department Head, David C. Brown, Reader, Charles Rich, Advisor, Candace L. Sidner, Advisor |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses (All Theses, All Years) |
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