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Dynamic Difficulty Adjustment for Maximized Engagement in Digital Games

Published: 03 April 2017 Publication History

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.

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      cover image ACM Other conferences
      WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion
      April 2017
      1738 pages
      ISBN:9781450349147

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      • IW3C2: International World Wide Web Conference Committee

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      Republic and Canton of Geneva, Switzerland

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      Published: 03 April 2017

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      Author Tags

      1. dynamic difficulty adjustment
      2. player engagement optimization
      3. progression model

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      WWW '17 Companion Paper Acceptance Rate 164 of 966 submissions, 17%;
      Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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