General Dynamic Difficulty Adjustment System for Major Game Genres

Qingwei Mi, Tianhan Gao

Abstract: Dynamic difficulty adjustment (DDA) is a research hotspot in the field of artificial intelligence (AI) in games. This paper designs and implements a general DDA system based on the flow to improve the status of the existing DDA methods highly specialized. The system proposed can be widely applied to major game genres in the game industry effectively. Improvement of parameters after introducing DDA proves the system’s high adaptability. Advantages on mean total score greater demonstrate that the system has a better player experience by inviting players to participate in the Game Engagement Questionnaires (GEQ). The soundness and generality of the system can provide a complete solution for optimizing the player’s gaming experience, thus supporting game designers and developers to achieve or port core AI systems of games more efficiently.