Novel Dynamic Difficulty Adjustment Methods for Niche Games

Qingwei Mi, Tianhan Gao

Abstract: As a research hotspot in Game Artificial Intelligence (Game AI), Dynamic difficulty adjustment (DDA) is a technology that adapts the game’s challenge to match the player’s skill. DDA is the core mechanic to provide continuous motivation and immersion to players during game design and development. This paper proposes general methods for niche games to improve the current research system of DDA. Advantages on adaptive parameters, gameplay time, and Immersive Experience Questionnaire (IEQ) results demonstrate the effectiveness in enhancing player experience and retention of the proposed methods with a high adaptability. The robust DDA system can help game designers to ensure experience and avoid churn of players.