2017 DynamicDifficultyAdjustmentforM

• (Xue et al., 2017) ⇒ Su Xue, Meng Wu, John Kolen, Navid Aghdaie, and Kazi A. Zaman. (2017). “Dynamic Difficulty Adjustment for Maximized Engagement in Digital Games.” In: Proceedings of the 26th International Conference on World Wide Web Companion. ISBN:978-1-4503-4914-7 doi:10.1145/3041021.3054170

Subject Headings: Video Game Player Engagement.

Cited By

• http://scholar.google.com/scholar?q=%222017%22+Dynamic+Difficulty+Adjustment+for+Maximized+Engagement+in+Digital+Games
• http://dl.acm.org/citation.cfm?id=3041021.3054170&preflayout=flat#citedby

Quotes

Abstract

Dynamic difficulty adjustment (DDA) is a technique for adaptively changing a game to make it easier or harder. A common paradigm to achieve DDA is through heuristic prediction and intervention, adjusting game difficulty once undesirable player states (e.g., boredom or frustration) are observed. Without quantitative objectives, it is impossible to optimize the strength of intervention and achieve the best effectiveness. In this paper, we propose a DDA framework with a global optimization objective of maximizing a player's engagement throughout the entire game. Using level-based games as our example, we model a player's progression as a probabilistic graph. Dynamic difficulty reduces to optimizing transition probabilities to maximize a player's stay time in the progression graph. We have successfully developed a system that applies this technique in multiple games by Electronic Arts, Inc., and have observed up to 9% improvement in player engagement with a neutral impact on monetization.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2017 DynamicDifficultyAdjustmentforM	Su Xue Meng Wu John Kolen Navid Aghdaie Kazi A. Zaman			Dynamic Difficulty Adjustment for Maximized Engagement in Digital Games				10.1145/3041021.3054170		2017