SoCS: Creation of a Framework for Computational Gaming

SoCS：创建计算游戏框架

• 批准号: 0968566
• 负责人: Anind Dey
• 金额: $ 70.5万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2014-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968566&HistoricalAwards=false
• 关键词: SoCS; Creation; Framework; Computational; Gaming

Leveraging crowdsourcing to collect data is becoming more common. Human Computation, in particular, has looked at how to use artificial intelligence on data collected from people playing games, to validate that useful data has been collected on a very large scale. This work will investigate a new form of artificial-intelligence based crowdsourced games called Computational Gaming, in which questions will be posed without knowing what the answers are beforehand. Questions that require human judgment will be posed in the context of a game, and machine learning will be used to determine what questions to pose to which players and how to determine whether the responses are valid.Intellectual Merit. This project will demonstrate the validity of Computational Gaming through two examples in text and image labeling, delineating a set of guiding design principles for building and evaluating future Computational Gaming designs, and producing a toolkit that supports and encourages the use of these design principles for building Computational Gaming systems.Potential Broader Impacts. The project will create, both more quickly and more cheaply, databases of human-labeled data; it will also do so for a wider variety of problems than currently exists. The framework and toolkit for Computational Gaming will be valuable for game designers, for researchers in many domains that need labeled data, and for the users for whom the research is being conducted.

利用众包收集数据正变得越来越普遍。特别是，人类计算研究了如何使用人工智能来处理从玩游戏的人那里收集的数据，以验证已经大规模收集了有用的数据。这项工作将研究一种新形式的基于人工智能的众包游戏，称为计算游戏，其中问题将在事先不知道答案的情况下提出。需要人类判断的问题将在游戏的背景下提出，机器学习将用于确定向哪些玩家提出什么问题以及如何确定回答是否有效。智力优势。该项目将通过文本和图像标签中的两个示例来证明计算游戏的有效性，描绘一套用于构建和评估未来计算游戏设计的指导设计原则，并制作一个支持和鼓励使用这些设计原则的工具包来构建计算游戏系统。潜在的更广泛影响。该项目将更快、更便宜地创建人类标记数据的数据库;它还将为比目前存在的更广泛的问题提供帮助。计算游戏的框架和工具包对于游戏设计者、需要标记数据的许多领域的研究人员以及正在进行研究的用户来说都是有价值的。