Using Mechanics to Reduce the Effectiveness of Min-Maxing in Role-Playing Games

利用机制降低角色扮演游戏中最小最大化的有效性

• 批准号: 2593951
• 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: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2593951
• 关键词: Using; Mechanics; Reduce; Effectiveness; Min

Min-maxing in role-playing games is creating a character with maximum positive traits and minimal negative ones. If min-maxing creates significantly optimal playstyles for a game, it can create a negative social effect where players deemed to be not following them can be ostracised from the community. From this I wish to see how mechanics can be used to create a role-playing game where min-maxed character builds provide no significant advantage over other builds. To achieve this, I will focus on developing a simulator which AI agents can use to create min-maxed characters, which are subsequently used to evaluate the effectives of mechanics in helping prevent an optimal playstyle from emerging. This research will help to create more creative and balanced RPGs, which will allow for a wider variety of playstyles and a more inclusive social environment.

角色扮演游戏中的“最小最大化”是指创造一个具有最大积极特征和最小消极特征的角色。如果“最小最大化”为游戏创造了显着的最佳游戏风格，它可能会产生负面的社会影响，被认为不遵循它们的玩家可能会被社区排斥。由此，我希望了解如何使用机制来创建角色扮演游戏，其中最小最大角色构建与其他构建相比没有显着优势。为了实现这一目标，我将专注于开发一个模拟器，人工智能代理可以使用它来创建最小最大角色，随后将其用于评估机制的有效性，以帮助防止最佳游戏风格的出现。这项研究将有助于创造更具创意和平衡的角色扮演游戏，从而实现更广泛的游戏风格和更具包容性的社交环境。