Incongruity-Based Adaptive Game Balancing
Commercial games possess various methods of game balancing. Each of them modifies the game’s entertainment value for players of different skill levels. This paper deals with one of them, viz. a way of automatically adapting a game’s balance which is based on the theory of incongruity. We tested our approach on a group of subjects, who played a game with three difficulty settings. The idea is to maintain a specific difference in incongruity automatically. We tested our idea extensively and may report that the results coincide with the theory of incongruity as far as positive incongruity is concerned. The main conclusion is that, owing to our automatically maintained balanced difficulty setting, we can avoid that a game becomes boring or frustrating.
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- 1.Beume, N., Danielsiek, H., Eichhorn, C., Naujoks, B., Preuss, M., Stiller, K., Wessing, S.: Measuring Flow as Concept for Detecting Game Fun in the Pac-Man Game. In: Proc. 2008 Congress on Evolutionary Computation (CEC 2008) within Fifth IEEE World Congress on Computational Intelligence (WCCI 2008). IEEE, Los Alamitos (2008)Google Scholar
- 2.Csikszentmihalyi, M., Csikszentmihalyi, I.: Introduction to Part IV in Optimal Experience: Psychological Studies of Flow in Consciousness. Cambridge University Press, Cambridge (1988)Google Scholar
- 3.Charles, D., Black, M.: Dynamic Player Modelling: A Framework for Player-Centric Games. In: Mehdi, Q., Gough, N.E., Natkin, S. (eds.) Computer Games: Artificial Intelligence, Design and Education, pp. 29–35. University of Wolverhampton, Wolverhampton (2004)Google Scholar
- 4.Hunicke, R., Chapman, V.: AI for Dynamic Difficulty Adjustment in Games. In: Proceedings of the Challenges in Game AI Workshop, 19th Nineteenth National Conference on Artificial Intelligence. AAAI 2004 (2004)Google Scholar
- 5.Iida, H., Takeshita, N., Yoshimura, J.: A Metric for Entertainment of Boardgames: Its Implication for Evolution of Chess Variants. In: Nakatsu, R., Hoshino, J. (eds.) Entertainment Computing: Technologies and Applications, pp. 659–672. Kluwer Academic Publishers, Boston (2002)Google Scholar
- 6.Likert, R.: A Technique for the Measurement of Attitudes. Archives of Psychology, New York (1932)Google Scholar
- 7.Rauterberg, M.: About a framework for information and information processing of learning systems. In: Falkenberg, E., Hesse, W., Olive, A. (eds.) Information System Concepts–Towards a consolidation of views (IFIP Working Group 8.1), pp. 54–69. Chapman and Hall, London (1995)Google Scholar
- 8.Spronck, P., Sprinkhuizen-Kuyper, I., Postma, E.: Difficulty Scaling of Game AI. In: Proceedings of the 5th Internactional Conference on Intelligent Games and Simulation (GAME-ON 2004), pp. 33–37 (2004)Google Scholar
- 9.Yannakakis, G.N.: How to Model and Augment Player Satisfaction: A Review. In: Proceedings of the 1st Workshop on Child, Computer and Interaction. ICMI 2008, Chania, Crete, October 2008. ACM Press, New York (2008)Google Scholar