Dynamic difficulty adjustment systems for various game genres

• Authors: Dziedzic Dagmara

Title variants

PL

Systemy dynamicznego wyważania rozgrywki wykorzystywane w różnych gatunkach gier

• Languages of publication: EN

Abstracts

EN

Creating a video game that is engaging for a large number of players is not an easy task. This problem is often associated with adjusting the gameplay’s difficulty to the skills of a specific player. As a result, the game is neither too easy nor too difficult, so the player does not feel bored or frustrated. In recent years, a number of systems which implement the balancing procedures for dynamic gameplay have been created for different genres of games. However, in the literature, no universal understanding of the concept of difficulty has been proposed. This article is an attempt to systematize the concept (used in systems with dynamic difficulty adjustment) and the methods of its evaluation. For this purpose, this paper will present a classification of video games based on the aspects of the game that are most closely connected with the difficulty of each game genre.

PL

Stworzenie gry wideo, która byłaby angażująca dla dużej liczby graczy, nie jest prostym zadaniem. Problem ten często wiąże się z dostosowaniem trudności rozgrywki do umiejętności konkretnego gracza. Dzięki temu gra nie okazuje się ani za łatwa, ani za trudna, przez co gracz nie czuje się znudzony czy sfrustrowany. W ciągu ostatnich lat powstało wiele implementacji systemów dynamicznego wyważania rozgrywki w różnych gatunkach gier. W literaturze próżno jednak szukać uniwersalnego rozumienia zagadnienia trudności gry. Niniejszy artykuł stanowi próbę usystematyzowania tej właściwości gier (wykorzystywanej przez systemy dynamicznego wyważania rozgrywki) oraz metod jej ewaluacji. W tym celu zostanie przedstawiona klasyfikacja gier wideo oparta na aspektach rozgrywki, któ- re mają największy związek z trudnością poszczególnych gatunków gier.

Keywords

EN

Dynamic Difficulty Adjustment (DDA); board games; video games; game typology

PL

dynamiczne wyważanie rozgrywki; gry planszowe; gry wideo; typologia gier

• Publisher: Polskie Towarzystwo Badania Gier (Games Research Association of Poland)
• Journal: Homo Ludens
• Year: 2016
• Issue: 1(9)
• Pages: 35-51
• Document type: article

Dates

published

2016

Contributors

author

Dziedzic Dagmara

• Uniwersytet im. Adama Mickiewicza w Poznaniu

References

• Aarseth, E., Smedstad, S. M., Sunnanå, L. (2003). A  multi-dimensional typology of games. In: M. Copier, J. Raessens (eds.), Level Up: Digital Games Research Conference Proceedings, 4–6 November 2003, Utrecht University (p. 48–53). Utrecht: Utrecht University.
• Andrade, G., Ramalho, G., Gomes, A. S., Corruble, V. (2006). Dynamic Game Balancing: An Evaluation of User Satisfaction. In: J. Laird, J. Schaeffer (eds.), Proceedings of the Second Artificial Intelligence and Interactive Digital Entertainment Conference (p. 3–8). Menlo Park, California: AAAI Press. Online: <http://www.aaai.org/Papers/AIIDE/2006/AIIDE06-005.pdf>. Access date: 7 November 2016.
• Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York: Harper and Row.
• Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. New York: Harper and Row.
• Goetschalckx, R., Missura, O., Hoey, J., Gärtner, T. (2010). Games with Dynamic Difficulty Adjustment using POMDPs. Online: <http://cs.uwaterloo.ca/~jhoey/papers/goetschalckx_mlg.pdf>. Access date: 7 November 2016.
• Guid, M., Bratko, I. (2013). Search-Based Estimation of Problem Difficulty for Humans. In: H. C. Lane, K.Yacef, J. Mostow, P. Pavlik (eds.), Artificial Intelligence in Education. 16th International Conference, AIED 2013, Memphis,TN, USA, July 9–13, 2013. Proceedings (p. 860–863). Springer. Online: <http://ailab.si/matej/doc/Search-Base_Estimation_of_Problem_Difficulty.pdf>. Access date: 8 November 2016.
• Huizinga, J. (1950). Homo Ludens: A  Study of the Play Element in Culture. Boston: Beacon Press.
• Hristova, D., Guid, M., Bratko, I. (2014). Assessing the Difficulty of Chess Tactical Problems. International Journal on Advances in Intelligent Systems, 7(3/4), 728–738. Online: <http://ailab.si/matej/doc/Assessing_the_Difficulty_of_Chess_Tactical_Problems.pdf>. Access date: 8 November 2016.
• Hunicke, R., Chapman, V. (2004). AI for Dynamic Difficulty Adjustment in Games. In: D. Fu, S.Henke, J.Orkin (eds.), Challenges in Game Artificial Intelligence: Papers from the AAAI Workshop (p. 91–96). Menlo Park, California: AAAI Press. Online: <http://www.cs.northwestern.edu/~hunicke/pubs/Hamlet.pdf>. Access date: 8 November 2016.
• Hunicke, R. (2005). The Case for Dynamic Difficulty Adjustment in Games. In: N. Lee (ed.), Proceedings of the 2005 ACM SIGCHI International Conference on Advances in Computer Entertainment Technology: Valencia, Spain, June 15–17 (p. 429–433). New York: ACM Press.
• Juul, J. (2009). Fear of Failing? The Many Meanings of Difficulty in Video Games. In: M. J. P.Wolf, B. Perron (eds.), The Video Game Theory Reader 2 (p. 237–252). New York: Routledge. Online: <http://www.jesperjuul.net/text/fearoffailing>. Access date: 8 November 2016.
• Juul, J. (2003). The Game, the Player, the World: Looking for a  Heart of Gameness. In: M. Copier, J. Raessens (eds.), Level Up: Digital Games Research Conference Proceedings, 4–6 November 2003, Utrecht University (p. 30–45). Utrecht: Utrecht University. Online: <http://www.jesperjuul.net/text/gameplayerworld>. Access date: 8 November 2016.
• Malone, T. W. (1980). What Make Things Fun to Learn? A Study of Intrinsically Motivating Computer Games. Pao Alto, California: XeroX Research Center.
• Missura, O. (2015). Dynamic Difficulty Adjustment. Bonn: unpublished PhD thesis. Online: <http://hss.ulb.uni-bonn.de/2015/4144/4144.pdf>. Access date: 22 May 2016.
• Missura, O., Gärtner, T. (2008). Online Adaptive Agent for “Connect Four”. In: M. Zhou (ed.), Proceedings of the 4th International Conference on Games Research and Development CyberGames 2008: Beijing, China, 27–30 October 2008 (p. 1–8). Beijing: Tsinghua University Press. Online: <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.478.3766&rep=rep1&type=pdf>. Access date: 8 November 2016.
• Pinto, P. (28 July 2002). Introducing the Min-Max Algorithm. Online: <http://www.progtools.org/games/tutorials/ai_contest/minmax_contest.pdf>. Access date: 9 December 2015.
• Quick, J. M., Atkinson, R. K., Lin, L. (2012). The Gameplay Enjoyment Model. International Journal of Gaming and Computer-Mediated Simulations, 4(4), 64–80. Online: <http://angle.lab.asu.edu/site/wp-content/uploads/2013/03/QuickAtkinsonLin_2012_IJGCMS_GEM.pdf>. Access date: 8 November 2016.
• Rogers, S. (2010). Level Up!: The Guide to Great Video Game Design. Chichester: Wiley
• Salen, K., Zimmerman, E. (2003). Rules of Play: Game Design Fundamentals. Cambridge: MIT Press.
• Sherry, J. L., Lucas, K., Greenberg, B. S., Lachlan, K. (2006). Video Game Uses and Gratifications as Predictors of Use and Game Preference. In: P.Vorderer, J. Bryant (eds.), Playing Computer Games: Motives, Responses, and Consequences (p. 213–224). Mahwah, New Jersey: Lawrence Erlbaum Associates. Online: <http://icagames.comm.msu.edu/vgu%26g.pdf>. Access date: 8 November 2016.
• Sutoyo, R., Winata, D., Oliviani, K., Supriyadi, D. M. (2015). Dynamic Difficulty Adjustment in Tower Defence. Procedia Computer Science, 59(1), 435–444. Online: <http://www.sciencedirect.com/science/article/pii/S187705091502092X>. Access date: 8 November 2016.
• Turocy, T. L., von Stengel, B. (8  October 2001). Game Theory. Online: <http://www.cdam.lse.ac.uk/Reports/Files/cdam-2001-09.pdf>. Access date: 8 November 2016.

Identifiers

ISSN

2080-4555