The balance of game content significantly impacts the gaming experience. Unbalanced game content diminishes engagement or increases frustration because of repetitive failure. Although game designers intend to adjust the difficulty of game content, this is a repetitive, labor-intensive, and challenging process, especially for commercial-level games with extensive content. To address this issue, the game research community has explored automated game balancing using artificial intelligence (AI) techniques. However, previous studies have focused on limited game content and did not consider the importance of the generalization ability of playtesting agents when encountering content changes. In this study, we propose RaidEnv, a new game simulator that includes diverse and customizable content for the boss raid scenario in MMORPG games. Additionally, we design two benchmarks for the boss raid scenario that can aid in the practical application of game AI. These benchmarks address two open problems in automatic content balancing, and we introduce two evaluation metrics to provide guidance for AI in automatic content balancing. This novel game research platform expands the frontiers of automatic game balancing problems and offers a framework within a realistic game production pipeline.

本研究提出了一个新的游戏模拟器——RaidEnv，并在其中设计了两个基准测试，以解决自动游戏平衡中的两个开放性问题，并引入了两个评估指标，为自动游戏平衡的AI提供指导，该创新性的游戏研究平台扩展了自动游戏平衡问题的前沿，并提供了一个在现实游戏生产流程中的框架。

RaidEnv:自动内容平衡探索Boss Raid游戏的新挑战