EAGER: Understanding Social Behavior in Real-Time Strategy Games

EAGER：了解实时策略游戏中的社交行为

• 批准号: 0948123
• 负责人: Jennifer Golbeck
• 金额: $ 19.62万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0948123&HistoricalAwards=false
• 关键词: EAGER; Understanding; Social; Behavior; Real

This is a study of how people make decisions in dynamic, social environments, achieving a methodological innovation by using online real-time strategy (RTS) games as laboratories for studying human behavior. Investigation into social interactions has been discussed in the context of virtual worlds and online role-playing games, but not in RTS games, nor have researchers yet developed the data-collection techniques or theoretical principles for doing research in this important sector of human-centered computing. In addition to their entertainment value, RTS games have emerged to become virtual platforms that simulate real-world, real-time physics, scenarios, characters, and strategies. Particularly, multi-player online RTS games are providing a new model of human interaction that is in line with decision theory, game theory, planning, learning, and other concepts from research fields such as Computer Science, Artificial Intelligence, Economics, and Behavioral Sciences.This research will study users' social strategies in RTS games in three major ways: developing a gaming environment, a user study with experiments, and an automated learning approach. The game will present users with a series of missions to be accomplished, and users will receive points for successful completion. In early stages these missions can be accomplished alone and with little effort, but as the player progresses they will require alliances with others. The first phase of user studies will involve a qualitative analysis of user behaviors, identifying specific points in the game when users must make decisions where the social relationships will be important factors. This qualitative analysis will be followed by a quantitative analysis of the players' performance, developing techniques for measuring the payoffs from each action. Once players begin developing strong alliances, a set of experiments will analyze their reasoning when making strategic decisions. This will include measurements of social tie strength, structural social network features, the past history of interactions, and evolutionary simulations of strategies. The final phase of research will involve controlled experiments with users, presenting them with situations where they have to make a decision that requires consideration of the social structure.This project will make software, test suites, documentation, and teaching materials freely available on the Internet. Decision making is an important problem in artificial intelligence, and effective decision-making is important in all kinds of organizations and real-world applications. This research could provide the theoretical and experimental basis for developing practical algorithms and applications for social decision making, to make it easier for the organizations and the users of such applications in their decision-making process.

这是一项关于人们如何在动态的社会环境中做出决策的研究，通过使用在线实时策略（RTS）游戏作为研究人类行为的实验室，实现了方法上的创新。 对社会互动的研究已经在虚拟世界和在线角色扮演游戏的背景下进行了讨论，但不是在RTS游戏中，研究人员也还没有开发出数据收集技术或理论原则，用于在以人为中心的计算这一重要领域进行研究。除了娱乐价值，RTS游戏已经成为模拟现实世界的虚拟平台，实时物理，场景，角色和策略。特别是多人在线即时战略游戏提供了一种新的人类互动模式，这种模式符合决策论、博弈论、规划、学习以及计算机科学、人工智能、经济学和行为科学等研究领域的其他概念。本研究将从三个主要方面研究用户在即时战略游戏中的社交策略：开发一个游戏环境，一个用户研究实验，和一个自动学习方法。 游戏将为用户提供一系列需要完成的任务，用户成功完成任务将获得积分。在早期阶段，这些任务可以单独完成，几乎不费力气，但随着玩家的进步，他们将需要与其他人结盟。 用户研究的第一阶段将涉及对用户行为的定性分析，确定游戏中用户必须做出决策的特定点，其中社交关系将是重要因素。 在定性分析之后，将对参与者的表现进行定量分析，开发衡量每个行动收益的技术。 一旦玩家开始发展强大的联盟，一组实验将分析他们在做出战略决策时的推理。这将包括社会关系强度的测量，结构化的社会网络特征，过去的互动历史，以及策略的进化模拟。 研究的最后阶段将涉及对用户的控制实验，向他们展示他们必须做出需要考虑社会结构的决定的情况。该项目将在互联网上免费提供软件、测试套件、文档和教学材料。决策是人工智能领域的一个重要问题，有效的决策在各种组织和实际应用中都很重要。该研究为开发实用的社会决策算法和应用提供了理论和实验基础，使社会决策的组织和用户在决策过程中更加方便。