Towards better personas in gaming : Contract based expert systems

J. A. Brown
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引用次数: 3

Abstract

Recent evaluations of Procedural Content Generation (PCG) methods have examined the use of personas as part of there evaluative functions. Personas, models of a user, have a number of complaints leveled against them by researchers as to their use as design tools: that there is poor empirical proof that they improve the design process, poor definitions lead to them not modeling actual uses, and they do not give any quantitative information for evaluation using a scientific approach. Examined is a framework in which a persona is not just defined as a model of a user, but is a contract list of player goals and actions available in the game. By defining a persona as a goal driven AI, it joins the idea of personas with a more qualitative evaluative method as well as not allowing developers to apply their own biases. Further, it allows for a persona to work beyond the design stage of the development, and into the maintenance stages. Taking into account game-play telemetry, it allows for personas to be used as tools for lessons learned for future developments.
面向游戏中更好的角色:基于契约的专家系统
最近对程序内容生成(PCG)方法的评估检查了角色作为评估功能的一部分的使用。作为用户模型的人物角色,研究者对其作为设计工具的使用提出了许多抱怨:缺乏经验证据证明它们改善了设计过程,糟糕的定义导致它们无法对实际使用进行建模,并且它们没有提供任何定量信息用于使用科学方法进行评估。在这个框架中,角色不仅被定义为用户的模型,而且是游戏中玩家目标和行动的契约列表。通过将角色定义为目标驱动的AI,它将角色概念与更定性的评估方法结合在一起,并且不允许开发人员应用自己的偏见。此外,它允许角色在开发的设计阶段之外工作,并进入维护阶段。考虑到游戏玩法遥测,它允许将人物角色用作吸取未来开发经验教训的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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