全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

A Framework for Adaptive Game Presenters with Emotions and Social Comments

DOI: 10.1155/2012/929814

Full-Text   Cite this paper   Add to My Lib

Abstract:

More and more games today try to adjust their gameplay to fit individual players; however, little work has been carried out in the same direction towards game presenter characters. Game commentary should take into account players' personalities along with game progress in order to achieve social player-adapted comment delivery that boosts the overall gameplay, engages the players, and stimulates the audience. In our work, we discuss a framework for implementing artificial game presenter characters that are based on game actions and players' social profiles in order to deliver knowledgeable, socially oriented comments. Moreover, the presented framework supports emotional facial expressions for the presenters, allowing them to convey their emotions and thus be more expressive than the majority of the commentary systems today. We prove our concept by developing a presenter character for multiplayer tabletop board games which we further put under usability evaluation with 9 players. The results showed that game sessions with presenter characters are preferred over the plain version of the game and that the majority of the players enjoy personalized social-oriented comments expressed via multimedia and emotions. 1. Introduction Our work on game presenter characters has been motivated by the popularity of television game shows and the lack of an analogy in the domain of computer-based entertainment. A significant amount of games played on TV shows are computer-based tabletop ones (Wheel of Fortune, Power of Ten, Who Wants to Be a Millionaire, etc.) with an overall setup emphasizing and amplifying social interaction. Game show presenters are identified as one of the 7 key attributes of appreciation of TV game shows [1]. From a social perspective, they are responsible for keeping the game socially engaging and stimulating. More specifically, presenters provoke social interaction in order to keep the players and the audience constantly motivated and alerted about the game progress. For this purpose, they rely on individual player profiles, current challenge, previous performance, and statistics to provide feedback commonly involving humor, reward, sympathy, surprise, disappointment, enthusiasm, agony, and anticipation. Nowadays, more and more games incorporate artificial commentator systems (Pro Evolution Soccer Series [2], Buzz! [3], etc.). Such systems are based on game events and use prerecorded voices of actors, game commentators, and TV-show presenters in order to feel more realistic to players. Some of these games ask for player names, in order to use them

References

[1]  B. Gunter, “Understanding the appeal of TV game shows,” Zeitschrift Für Medienpsychologie, vol. 7, no. 2, pp. 87–106, 1995, PhycINFO.
[2]  Pro Evolution Soccer Series, http://en.wikipedia.org/wiki/Pro_Evolution_Soccer_(series).
[3]  Buzz! Game series, http://www.buzzthegame.com/en-gb/.
[4]  D. Voelz, E. Andrè, G. Herzog, and T. Rist, “Rocco: a RoboCup soccer commentator system,” in Proceedings of the ROBOCUP-98: ROBOT Soccer World Cup II, vol. 1604/1999 of Lecture Notes in Computer Science, no. 50-60, 1999.
[5]  E. Andrè, K. Binsted, K. Tanaka-Ishii, S. Luke, G. Herzog, and T. Rist, “Three RoboCup simulation league commentator systems,” AI Magazine, vol. 21, no. 1, pp. 57–65, 2000.
[6]  K. Binsted and S. Luke, “Character design for soccer commentary,” in RoboCup-98: Robot Soccer World Cup II, M. Asada and H. Kitano, Eds., vol. 1604 of Springer Lecture Notes in Computer Science, pp. 22–33, 2008.
[7]  C. Conati and M. Manske, “Evaluating adaptive feedback in an educational computer game,” in Intelligent Virtual Agents, vol. 5773/2009 of Lecture Notes in Computer Science, pp. 146–158, 2009.
[8]  C. Conati and M. Klawe, “Socially intelligent agents in educational games,” in Socially Intelligent Agents—Creating Relationships with Computers and Robots, K. Dautenhahn, et al., Ed., Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002.
[9]  C. Conati and X. Zhao, “Building and evaluating an intelligent pedagogical agent to improve the effectiveness of an educational game,” in Proceedings of the International Conference on Intelligent User Interfaces (IUI '04), pp. 6–13, Island of Madeira, Portugal, January 2004.
[10]  P. H. Tan, S. W. Ling, and X. Y. Ting, “Adaptive Digital Game-Based Learning Framework,” in Proceesings of 2nd International Conference on Digital Interactive Media and Entertainment and Arts (DIMEA '07), pp. 142–146, Perth, Western Australia, 2007.
[11]  S. M. Fisch, “Making educational computer games ‘educational’,” in Proceedings of the Interaction Design and Children (IDC '05), pp. 56–61, June 2005.
[12]  R. Hunicke and V. Chapman, “AI for dynamic difficulty adjustment in games,” in Proceedings of the 19th National Conference on Artificial Intelligence, pp. 91–96, usa, July 2004.
[13]  Resident Evil 5 Official Strategy Guide, “Prima Publishing,” 2009.
[14]  Mario Kart series, http://en.wikipedia.org/wiki/Mario_Kart.
[15]  Dynamic Game Difficulty Managing, http://en.wikipedia.org/wiki/Dynamic_game_difficulty_balancing#cite_ref-0.
[16]  P. Demasi and A. Cruz, “Online coevolution for action games,” in Proceedings of the 3rd International Conference on Intelligent Games and Simulation, pp. 113–120, London, UK, 2002.
[17]  C. Conati and M. Manske, “Adaptive feedback in an educational game for number factorization,” Frontiers in Artificial Intelligence and Applications, vol. 200, no. 1, pp. 581–583, 2009.
[18]  A. Gulz, M. Haake, and A. Silvervarg, “Extending a teachable agent with a social conversation module effects on student experiences and learning,” in Proceedings of The 15th International Conference on Artificial Intelligence in Education, vol. 6738/2011 of Lecture Notes in Computer Science, pp. 106–114, Auckland, New Zealand, 2011.
[19]  R. Imbert and A. de Antonio, “An emotional architecture for virtual characters,” in Proceedings of the International Conference on Virtual Storytelling (ICVS '05), Springer Lecture Notes in Computer Science, no. 3805, pp. 63–72, 2005.
[20]  K. M. Gilleade and A. Dix, “Using frustration in the design of adaptive videogames,” in Proceedings of the ACM SIGCHI International Conference on Advances in Computer Entertainment Technology (ACE '04), pp. 228–232, Singapore, 2004.
[21]  J. Sykes S, “Affective gaming: measuring emotion through the gamepad,” in Proceedings of the Extended Abstracts on Human Factors in Computing Systems (CHI EA '03 CHI '03), 2003.
[22]  S. Shahid, E. Krahmer, M. Swerts, W. A. Melder, and M. A. Neerincx, “You make me happy: using an adaptive affective interface to investigate the effect of social presence on positive emotion induction,” in Proceedings of the 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops (ACII '09), pp. 1–6, Amsterdam, The Netherlands, September 2009.
[23]  A. Savidis, M. Antona, and C. Stephanidis, “A decision-making specification language for verifiable user-interface adaptation logic,” International Journal of Software Engineering and Knowledge Engineering, vol. 15, no. 6, pp. 1063–1094, 2005.
[24]  J. Russell and G. Lemay, “Emotion concepts,” in Handbook of Emotion, M. Lewis and M. Haviland-Jones, Eds., Guilford Press, New York, NY, USA, 2000.
[25]  R. Likert, “A technique for the measurement of attitudes,” Archives of Psychology, vol. 22, no. 140, pp. 1–55, 1932.
[26]  A. Savidis and Y. Lilis, “Player-defined configurable soft dialogues: an extensible input system for tabletop games,” in Proceedings of the 5th ACM International Conference on Interactive Tabletops and Surfaces (ITS '10), pp. 287–288, November 2010.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133