Dynamic difficulty adjustment (DDA) is a highly significant research direction in game AI. Rubber-banding is one of the DDA techniques extensively used in racing games. This paper improves the poor adaptability of the rubber-banding system combined with the game design and development techniques. An Adaptive Rubber-Banding System (ARBS) based on ARBS relationship curve, modular mechanism, as well as detail processing schemes, is implemented in Unreal Engine 4. The paper builds various test programs and compares each system in terms of the number of players, gameplay mode, and track distance. Experimental results demonstrate that ARBS is more adaptive and provides a better experience for players. Game designers and developers are thus able to employ ARBS to design and implement AI systems suitable for racing games effectively.

中文翻译：

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赛车游戏动态难度调整的自适应橡皮筋系统

动态难度调整（DDA）是游戏AI中一个非常重要的研究方向。橡皮筋是赛车游戏中广泛使用的 DDA 技术之一。本文结合游戏设计和开发技术，改善了橡皮筋系统适应性差的问题。在虚幻引擎4中实现了基于ARBS关系曲线、模块化机制以及详细处理方案的自适应橡皮筋系统（ARBS）。本文构建了各种测试程序，并根据玩家数量对每个系统进行了比较，游戏模式和跟踪距离。实验结果表明，ARBS更具适应性，为玩家提供了更好的体验。因此，游戏设计师和开发人员能够使用 ARBS 来设计和实现适用于赛车游戏的 AI 系统。