The use of AI strategy data in redefining modern tabletop game design

AI策略数据的运用重新定义现代桌面游戏设计

• 批准号: 2890044
• 金额: --
• 依托单位: Queen Mary University of London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2890044
• 关键词: use; AI; strategy; data; redefining

With the evolution of tabletop games, they have become much more complex than their traditional counterparts (chess, go), they now have hidden information, a higher variety of components, and uncertainty as a few examples. This complexity is what made them thrive in the current world, but this also makes the creation of such games more difficult. This research use AI players to investigate different game strategies which can be evaluated through a series of metrics. We aim to investigate how to use existing metrics for strategy and create new ones to assist game design. The proposed contribution is two-fold: first, a tool that assists game designers in analyzing their game strategies; second, the development of new metrics for games focused on evaluating higher-level concepts such as player engagement and sellability. This will allow game designers to create better games and also assist players in achieving a better play experience.

随着桌面游戏的发展，它们变得比传统游戏（国际象棋、围棋）复杂得多，例如，它们现在具有隐藏信息、更多种类的组件和不确定性。这种复杂性使得它们在当今世界蓬勃发展，但这也使得此类游戏的创建变得更加困难。这项研究使用人工智能玩家来研究不同的游戏策略，这些策略可以通过一系列指标进行评估。我们的目标是研究如何使用现有的策略指标并创建新的指标来协助游戏设计。拟议的贡献有两个方面：首先，一个帮助游戏设计师分析其游戏策略的工具；其次，游戏新指标的开发侧重于评估更高层次的概念，例如玩家参与度和可售性。这将使游戏设计师能够创造出更好的游戏，并帮助玩家获得更好的游戏体验。