Advertisement

A Game-Based Corpus for Analysing the Interplay between Game Context and Player Experience

  • Noor Shaker
  • Stylianos Asteriadis
  • Georgios N. Yannakakis
  • Kostas Karpouzis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6975)

Abstract

Recognizing players’ affective state while playing video games has been the focus of many recent research studies. In this paper we describe the process that has been followed to build a corpus based on game events and recorded video sessions from human players while playing Super Mario Bros. We present different types of information that have been extracted from game context, player preferences and perception of the game, as well as user features, automatically extracted from video recordings. We run a number of initial experiments to analyse players’ behavior while playing video games as a case study of the possible use of the corpus.

Keywords

game-based corpus player behavior player’s affective state player experience 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Asteriadis, S., Tzouveli, P., Karpouzis, K., Kollias, S.: Estimation of behavioral user state based on eye gaze and head pose - application in an e-learning environment. In: Multimedia Tools and Applications, vol. 41(3), pp. 469–493. Springer, Heidelberg (2009)Google Scholar
  2. 2.
    Calleja, G.: In-Game From Immersion to Incorporation. MIT Press, USA (2011)Google Scholar
  3. 3.
    Conati, C.: Probabilistic assessment of users emotions in educational games. Applied Artificial Intelligence 16, 555–575 (2002)CrossRefGoogle Scholar
  4. 4.
    Csikszentmihalyi, M.: Flow: The Psychology of Optimal Experience. Harper Perennial (March 1991)Google Scholar
  5. 5.
    Höök, K.: Affective loop experiences – what are they? In: Oinas-Kukkonen, H., Hasle, P., Harjumaa, M., Segerståhl, K., Øhrstrøm, P. (eds.) PERSUASIVE 2008. LNCS, vol. 5033, pp. 1–12. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  6. 6.
    Hudlicka, E.: Affective computing for game design. In: GAMEON-NA 2008: Proceedings of the 4th Intl. North American Conference on Intelligent Games and Simulation, Montreal, Canada, pp. 5–12 (2008)Google Scholar
  7. 7.
    Ioannou, S., Caridakis, G., Karpouzis, K., Kollias, S.: Robust Feature Detection for Facial Expression Recognition. EURASIP Journal on Image and Video Processing 2007(2), 1–23 (2007)CrossRefGoogle Scholar
  8. 8.
    Isbister, K., Schaffer, N.: Game Usability: Advancing the Player Experience. Morgan Kaufmann, San Francisco (2008)Google Scholar
  9. 9.
    Koster, R.: A theory of fun for game design. Paraglyph press, Scottsdale (2004)Google Scholar
  10. 10.
    Leite, I., Pereira, A., Mascarenhas, S., Castellano, G., Martinho, C., Prada, R., Paiva, A.: Closing the loop: from affect recognition to empathic interaction. In: Proceedings of the 3rd International Workshop on Affective Interaction in Natural Environments, AFFINE 2010, pp. 43–48. ACM, New York (2010)Google Scholar
  11. 11.
    Malone, T.: What makes computer games fun (abstract only). In: Proceedings of the Joint Conference on Easier and More Productive Use Of Computer Systems (Part - II): Human Interface and the User Interface, CHI 1981, p. 143. ACM, New York (1981)CrossRefGoogle Scholar
  12. 12.
    Mandryk, R.L., Inkpen, K.M.: Physiological indicators for the evaluation of co-located collaborative play. In: Proceedings of the 2004 ACM Conference on Computer Supported Cooperative Work, CSCW 2004, pp. 102–111. ACM, New York (2004)CrossRefGoogle Scholar
  13. 13.
    Pagulayan, R.J., Keeker, K., Wixon, D., Romero, R.L., Fuller, T.: User-centered design in games. In: The Human-Computer Interaction Handbook, pp. 883–906. L. Erlbaum Associates Inc., Hillsdale (2003), http://portal.acm.org/citation.cfm?id=772072.772128Google Scholar
  14. 14.
    Pedersen, C., Togelius, J., Yannakakis, G.N.: Modeling player experience in super mario bros. In: CIG 2009: Proceedings of the 5th International Conference on Computational Intelligence and Games, pp. 132–139. IEEE Press, Piscataway (2009)Google Scholar
  15. 15.
    Pedersen, C., Togelius, J., Yannakakis, G.N.: Modeling player experience for content creation. IEEE Transactions on Computational Intelligence and AI in Games 2(1), 54–67 (2010)CrossRefGoogle Scholar
  16. 16.
    Picard, R.W.: Affective Computing. The MIT Press, Cambridge (1997)CrossRefGoogle Scholar
  17. 17.
    Picard, R.W., Vyzas, E., Healey, J.: Toward machine emotional intelligence: Analysis of affective physiological state. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 1175–1191 (2001)CrossRefGoogle Scholar
  18. 18.
    Poels, K., IJsselsteijn, W.: Development and validation of the game experience questionnaire. In: FUGA Workshop Mini-Symposium, Helsinki, Finland (2008)Google Scholar
  19. 19.
    Shaker, N., Yannakakis, G.N., Togelius, J.: Towards Automatic Personalized Content Generation for Platform Games. In: Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE). AAAI Press, Menlo Park (2010)Google Scholar
  20. 20.
    Shaker, N., Yannakakis, G.N., Togelius, J.: Feature Analysis for Modeling Game Content Quality. In: IEEE Transactions on Computational Intelligence and AI in Games. IEEE Press, Los Alamitos (2011)Google Scholar
  21. 21.
    Sidner, C., Lee, C., Kidd, C., Lesh, N., Rich, C.: Explorations in engagement for humans and robots. Artificial Intelligence 166(1-2), 140–164 (2005)CrossRefGoogle Scholar
  22. 22.
    Smith, P., Shah, M., da Vitoria Lobo, N.: Determining driver visual attention with one camera. IEEE Transactions on Intelligent Transportation Systems 4(4), 205–218 (2003)CrossRefGoogle Scholar
  23. 23.
    Yannakakis, G.N.: Preference Learning for Affective Modeling. In: Proceedings of the Int. Conf. on Affective Computing and Intelligent Interaction, pp. 126–131. IEEE, Amsterdam (2009)Google Scholar
  24. 24.
    Yannakakis, G.N., Maragoudakis, M., Hallam, J.: Preference learning for cognitive modeling: a case study on entertainment preferences. Trans. Sys. Man Cyber. Part A 39, 1165–1175 (2009)CrossRefGoogle Scholar
  25. 25.
    Yannakakis, G.N., Togelius, J.: Experience-driven Procedural Content Generation. IEEE Transactions on Affective Computing (in print, 2011)Google Scholar
  26. 26.
    Yannakakis, G., Hallam, J.: Real-time adaptation of augmented-reality games for optimizing player satisfaction. In: IEEE Symposium on Computational Intelligence and Games, CIG 2008, pp. 103–110 (December 2008)Google Scholar
  27. 27.
    Yannakakis, G., Hallam, J.: Real-time Game Adaptation for Optimizing Player Satisfaction. IEEE Transactions on Computational Intelligence and AI in Games 1(2), 121–133 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Noor Shaker
    • 1
  • Stylianos Asteriadis
    • 2
  • Georgios N. Yannakakis
    • 1
  • Kostas Karpouzis
    • 2
  1. 1.IT University of CopenhagenCopenhagenDenmark
  2. 2.National Technical University of AthensAthensGreece

Personalised recommendations